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Lampinen B, Szczepankiewicz F, Lätt J, Knutsson L, Mårtensson J, Björkman-Burtscher IM, van Westen D, Sundgren PC, Ståhlberg F, Nilsson M. Probing brain tissue microstructure with MRI: principles, challenges, and the role of multidimensional diffusion-relaxation encoding. Neuroimage 2023; 282:120338. [PMID: 37598814 DOI: 10.1016/j.neuroimage.2023.120338] [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: 02/02/2023] [Revised: 06/30/2023] [Accepted: 08/17/2023] [Indexed: 08/22/2023] Open
Abstract
Diffusion MRI uses the random displacement of water molecules to sensitize the signal to brain microstructure and to properties such as the density and shape of cells. Microstructure modeling techniques aim to estimate these properties from acquired data by separating the signal between virtual tissue 'compartments' such as the intra-neurite and the extra-cellular space. A key challenge is that the diffusion MRI signal is relatively featureless compared with the complexity of brain tissue. Another challenge is that the tissue microstructure is wildly different within the gray and white matter of the brain. In this review, we use results from multidimensional diffusion encoding techniques to discuss these challenges and their tentative solutions. Multidimensional encoding increases the information content of the data by varying not only the b-value and the encoding direction but also additional experimental parameters such as the shape of the b-tensor and the echo time. Three main insights have emerged from such encoding. First, multidimensional data contradict common model assumptions on diffusion and T2 relaxation, and illustrates how the use of these assumptions cause erroneous interpretations in both healthy brain and pathology. Second, many model assumptions can be dispensed with if data are acquired with multidimensional encoding. The necessary data can be easily acquired in vivo using protocols optimized to minimize Cramér-Rao lower bounds. Third, microscopic diffusion anisotropy reflects the presence of axons but not dendrites. This insight stands in contrast to current 'neurite models' of brain tissue, which assume that axons in white matter and dendrites in gray matter feature highly similar diffusion. Nevertheless, as an axon-based contrast, microscopic anisotropy can differentiate gray and white matter when myelin alterations confound conventional MRI contrasts.
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Affiliation(s)
- Björn Lampinen
- Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden.
| | | | - Jimmy Lätt
- Department of Medical Imaging and Physiology, Skåne University Hospital Lund, Lund, Sweden
| | - Linda Knutsson
- Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Johan Mårtensson
- Clinical Sciences Lund, Logopedics, Phoniatrics and Audiology, Lund University, Lund, Sweden
| | - Isabella M Björkman-Burtscher
- Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Danielle van Westen
- Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden; Department of Medical Imaging and Physiology, Skåne University Hospital Lund, Lund, Sweden
| | - Pia C Sundgren
- Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden; Department of Medical Imaging and Physiology, Skåne University Hospital Lund, Lund, Sweden; Lund University BioImaging Centre (LBIC), Lund University, Lund, Sweden
| | - Freddy Ståhlberg
- Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden; Clinical Sciences Lund, Medical Radiation Physics, Lund University, Lund, Sweden
| | - Markus Nilsson
- Clinical Sciences Lund, Diagnostic Radiology, Lund University, Lund, Sweden
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Fritz FJ, Mordhorst L, Ashtarayeh M, Periquito J, Pohlmann A, Morawski M, Jaeger C, Niendorf T, Pine KJ, Callaghan MF, Weiskopf N, Mohammadi S. Fiber-orientation independent component of R 2* obtained from single-orientation MRI measurements in simulations and a post-mortem human optic chiasm. Front Neurosci 2023; 17:1133086. [PMID: 37694109 PMCID: PMC10491021 DOI: 10.3389/fnins.2023.1133086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 08/04/2023] [Indexed: 09/12/2023] Open
Abstract
The effective transverse relaxation rate (R2*) is sensitive to the microstructure of the human brain like the g-ratio which characterises the relative myelination of axons. However, the fibre-orientation dependence of R2* degrades its reproducibility and any microstructural derivative measure. To estimate its orientation-independent part (R2,iso*) from single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientations, a second-order polynomial in time model (hereafter M2) can be used. Its linear time-dependent parameter, β1, can be biophysically related to R2,iso* when neglecting the myelin water (MW) signal in the hollow cylinder fibre model (HCFM). Here, we examined the performance of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We found that the fitted β1 can estimate R2,iso* using meGRE with long maximum-echo time (TEmax ≈ 54 ms), but not accurately captures its microscopic dependence on the g-ratio (error 84%). We proposed a new heuristic expression for β1 that reduced the error to 12% for ex vivo compartmental R2 values. Using the new expression, we could estimate an MW fraction of 0.14 for fibres with negligible dispersion in a fixed human optic chiasm for the ex vivo compartmental R2 values but not for the in vivo values. M2 and the HCFM-based simulations failed to explain the measured R2*-orientation-dependence around the magic angle for a typical in vivo meGRE protocol (with TEmax ≈ 18 ms). In conclusion, further validation and the development of movement-robust in vivo meGRE protocols with TEmax ≈ 54 ms are required before M2 can be used to estimate R2,iso* in subjects.
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Affiliation(s)
- Francisco J. Fritz
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Laurin Mordhorst
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Mohammad Ashtarayeh
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Joao Periquito
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Andreas Pohlmann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Markus Morawski
- Paul Flechsig Institute – Center for Neuropathology and Brain Research, University of Leipzig, Leipzig, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Carsten Jaeger
- Paul Flechsig Institute – Center for Neuropathology and Brain Research, University of Leipzig, Leipzig, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Kerrin J. Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - 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
| | - Siawoosh Mohammadi
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Max Planck Research Group MR Physics, Max Planck Institute for Human Development, Berlin, Germany
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3
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Gast H, Horowitz A, Krupnik R, Barazany D, Lifshits S, Ben-Amitay S, Assaf Y. A Method for In-Vivo Mapping of Axonal Diameter Distributions in the Human Brain Using Diffusion-Based Axonal Spectrum Imaging (AxSI). Neuroinformatics 2023; 21:469-482. [PMID: 37036548 PMCID: PMC10406702 DOI: 10.1007/s12021-023-09630-w] [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] [Accepted: 03/24/2023] [Indexed: 04/11/2023]
Abstract
In this paper we demonstrate a generalized and simplified pipeline called axonal spectrum imaging (AxSI) for in-vivo estimation of axonal characteristics in the human brain. Whole-brain estimation of the axon diameter, in-vivo and non-invasively, across all fiber systems will allow exploring uncharted aspects of brain structure and function relations with emphasis on connectivity and connectome analysis. While axon diameter mapping is important in and of itself, its correlation with conduction velocity will allow, for the first time, the explorations of information transfer mechanisms within the brain. We demonstrate various well-known aspects of axonal morphometry (e.g., the corpus callosum axon diameter variation) as well as other aspects that are less explored (e.g., axon diameter-based separation of the superior longitudinal fasciculus into segments). Moreover, we have created an MNI based mean axon diameter map over the entire brain for a large cohort of subjects providing the reference basis for future studies exploring relation between axon properties, its connectome representation, and other functional and behavioral aspects of the brain.
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Affiliation(s)
- Hila Gast
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
| | - Assaf Horowitz
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Ronnie Krupnik
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Daniel Barazany
- The Strauss center for neuroimaging, Tel Aviv University, Tel Aviv, Israel
| | - Shlomi Lifshits
- Department of Statistics and Operations Research, Faculty of Exact Sciences, Tel Aviv University, Tel-Aviv, Israel
| | - Shani Ben-Amitay
- School of Neurobiology, Biochemistry and Biophysics, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Yaniv Assaf
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- The Strauss center for neuroimaging, Tel Aviv University, Tel Aviv, Israel
- School of Neurobiology, Biochemistry and Biophysics, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
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4
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Liu F, Hu W, Sun Y, Shen Y, Zhou W, Dai Y, Gu L, Zhang M, Zhou Y. Exploration of Interstitial Fibrosis in Chronic Kidney Disease by Diffusion‐Relaxation Correlation Spectrum
MR
Imaging: A Preliminary Study. J Magn Reson Imaging 2022. [DOI: 10.1002/jmri.28535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 11/23/2022] Open
Affiliation(s)
- Fang Liu
- Department of Radiology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Wentao Hu
- Central Research Institute, United Imaging Healthcare Shanghai China
| | - Yawen Sun
- Department of Radiology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Yiwei Shen
- Department of Nephrology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Wenyan Zhou
- Department of Nephrology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Yongming Dai
- Central Research Institute, United Imaging Healthcare Shanghai China
| | - Leyi Gu
- Department of Nephrology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Minfang Zhang
- Department of Nephrology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
| | - Yan Zhou
- Department of Radiology Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai China
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5
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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 PMCID: PMC9121330 DOI: 10.1016/j.neuroimage.2022.118958] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [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 diffusion MRI 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 diffusion MRI 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, USA; 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, the Netherlands
| | - Mathias Davids
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; 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, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - 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, USA; Harvard Medical School, Boston, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | | | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Yi-Qiao Song
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; 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, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
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6
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Tax CMW, Kleban E, Chamberland M, Baraković M, Rudrapatna U, Jones DK. Measuring compartmental T 2-orientational dependence in human brain white matter using a tiltable RF coil and diffusion-T 2 correlation MRI. Neuroimage 2021; 236:117967. [PMID: 33845062 PMCID: PMC8270891 DOI: 10.1016/j.neuroimage.2021.117967] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 02/15/2021] [Accepted: 03/08/2021] [Indexed: 02/08/2023] Open
Abstract
The anisotropy of brain white matter microstructure manifests itself in orientational-dependence of various MRI contrasts, and can result in significant quantification biases if ignored. Understanding the origins of this orientation-dependence could enhance the interpretation of MRI signal changes in development, ageing and disease and ultimately improve clinical diagnosis. Using a novel experimental setup, this work studies the contributions of the intra- and extra-axonal water to the orientation-dependence of one of the most clinically-studied parameters, apparent transverse relaxation T2. Specifically, a tiltable receive coil is interfaced with an ultra-strong gradient MRI scanner to acquire multidimensional MRI data with an unprecedented range of acquisition parameters. Using this setup, compartmental T2 can be disentangled based on differences in diffusional-anisotropy, and its orientation-dependence further elucidated by re-orienting the head with respect to the main magnetic field B→0. A dependence of (compartmental) T2 on the fibre orientation w.r.t. B→0 was observed, and further quantified using characteristic representations for susceptibility- and magic angle effects. Across white matter, anisotropy effects were dominated by the extra-axonal water signal, while the intra-axonal water signal decay varied less with fibre-orientation. Moreover, the results suggest that the stronger extra-axonal T2 orientation-dependence is dominated by magnetic susceptibility effects (presumably from the myelin sheath) while the weaker intra-axonal T2 orientation-dependence may be driven by a combination of microstructural effects. Even though the current design of the tiltable coil only offers a modest range of angles, the results demonstrate an overall effect of tilt and serve as a proof-of-concept motivating further hardware development to facilitate experiments that explore orientational anisotropy. These observations have the potential to lead to white matter microstructural models with increased compartmental sensitivity to disease, and can have direct consequences for longitudinal and group-wise T2- and diffusion-MRI data analysis, where the effect of head-orientation in the scanner is commonly ignored.
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Affiliation(s)
- Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, UK; University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Elena Kleban
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Muhamed Baraković
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK; Signal Processing Laboratory 5, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland; Translational Imaging in Neurology Basel, Department of Biomedical Engineering, University Hospital Basel, Basel, Switzerland
| | - Umesh Rudrapatna
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK; Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
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7
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Eliav U, Shinar H, Navon G. Identification of water compartments in spinal cords by 2 H double quantum filtered NMR. NMR IN BIOMEDICINE 2021; 34:e4452. [PMID: 33345362 DOI: 10.1002/nbm.4452] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/24/2019] [Revised: 11/04/2020] [Accepted: 11/09/2020] [Indexed: 06/12/2023]
Abstract
In 2 H double quantum filtered (DQF) NMR, the various water compartments are characterized by their different residual quadrupolar interactions. The spectral separation between the different signals enables the measurement of the relaxation of each compartment and the magnetization transfer (MT) between them. In the current study, five water compartments were identified in the 2 H DQF spectra of porcine spinal cord. The most prominent signal was the pair of satellites with a quadrupolar splitting of about 550 Hz. 2 H DQF MRI optimized for the 550 Hz quadrupolar splitting indicated that this signal originated mainly from the white matter and it was assigned to the myelin water. This splitting does not change upon changing the orientation of the spinal cord relative to the magnetic field, indicating a liquid crystalline nature. Another site exhibiting splitting of about 1500 Hz was assigned to collagenous connective tissue. The narrow central peak was assigned to a combination of intra- and inter-axonal water. The assignment of the other two sites is not certain and requires further study. The rates of MT between the various sites were recorded.
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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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8
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Benjamini D, Basser PJ. Multidimensional correlation MRI. NMR IN BIOMEDICINE 2020; 33:e4226. [PMID: 31909516 PMCID: PMC11062766 DOI: 10.1002/nbm.4226] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 10/24/2019] [Accepted: 10/28/2019] [Indexed: 05/23/2023]
Abstract
Multidimensional correlation spectroscopy is emerging as a novel MRI modality that is well suited for microstructure and microdynamic imaging studies, especially of biological specimens. Conventional MRI methods only provide voxel-averaged and mostly macroscopically averaged information; these methods cannot disentangle intra-voxel heterogeneity on the basis of both water mobility and local chemical interactions. By correlating multiple MR contrast mechanisms and processing the data in an integrated manner, correlation spectroscopy is able to resolve the distribution of water populations according to their chemical and physical interactions with the environment. The use of a non-parametric, phenomenological representation of the multidimensional MR signal makes no assumptions about tissue structure, thereby allowing the study of microscopic structure and composition of complex heterogeneous biological systems. However, until recently, vast data requirements have confined these types of measurement to non-localized NMR applications and prevented them from being widely and successfully used in conjunction with imaging. Recent groundbreaking advancements have allowed this powerful NMR methodology to be migrated to MRI, initiating its emergence as a promising imaging approach. This review is not intended to cover the entire field of multidimensional MR; instead, it focuses on pioneering imaging applications and the challenges involved. In addition, the background and motivation that have led to multidimensional correlation MR development are discussed, along with the basic underlying mathematical concepts. The goal of the present work is to provide the reader with a fundamental understanding of the techniques developed and their potential benefits, and to provide guidance to help refine future applications of this technology.
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Affiliation(s)
- Dan Benjamini
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
- Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation, Bethesda, MD, USA
| | - Peter J. Basser
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
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9
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Beaulieu C, Yip E, Low PB, Mädler B, Lebel CA, Siegel L, Mackay AL, Laule C. Myelin Water Imaging Demonstrates Lower Brain Myelination in Children and Adolescents With Poor Reading Ability. Front Hum Neurosci 2020; 14:568395. [PMID: 33192398 PMCID: PMC7596275 DOI: 10.3389/fnhum.2020.568395] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 08/31/2020] [Indexed: 01/18/2023] Open
Abstract
Magnetic resonance imaging (MRI) provides a means to non-invasively investigate the neurological links with dyslexia, a learning disability that affects one’s ability to read. Most previous brain MRI studies of dyslexia and reading skill have used structural or diffusion imaging to reveal regional brain abnormalities. However, volumetric and diffusion MRI lack specificity in their interpretation at the microstructural level. Myelin is a critical neural component for brain function and plasticity, and as such, deficits in myelin may impact reading ability. MRI can estimate myelin using myelin water fraction (MWF) imaging, which is based on evaluation of the proportion of short T2 myelin-associated water from multi-exponential T2 relaxation analysis, but has not yet been applied to the study of reading or dyslexia. In this study, MWF MRI, intelligence, and reading assessments were acquired in 20 participants aged 10–18 years with a wide range of reading ability to investigate the relationship between reading ability and myelination. Group comparisons showed markedly lower MWF by 16–69% in poor readers relative to good readers in the left and right thalamus, as well as the left posterior limb of the internal capsule, left/right anterior limb of the internal capsule, left/right centrum semiovale, and splenium of the corpus callosum. MWF over the entire group also correlated positively with three different reading scores in the bilateral thalamus as well as white matter, including the splenium of the corpus callosum, left posterior limb of the internal capsule, left anterior limb of the internal capsule, and left centrum semiovale. MWF imaging from T2 relaxation suggests that myelination, particularly in the bilateral thalamus, splenium, and left hemisphere white matter, plays a role in reading abilities. Myelin water imaging thus provides a potentially valuable in vivo imaging tool for the study of dyslexia and its remediation.
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Affiliation(s)
- Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, AB, Canada
| | - Eugene Yip
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Pauline B Low
- Department of Education and Counseling Psychology, University of British Columbia, Vancouver, BC, Canada
| | | | | | - Linda Siegel
- Department of Education and Counseling Psychology, University of British Columbia, Vancouver, BC, Canada
| | - Alex L Mackay
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada.,Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
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10
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Fricke SN, Seymour JD, Battistel MD, Freedberg DI, Eads CD, Augustine MP. Data processing in NMR relaxometry using the matrix pencil. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2020; 313:106704. [PMID: 32179433 DOI: 10.1016/j.jmr.2020.106704] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 02/12/2020] [Accepted: 02/28/2020] [Indexed: 06/10/2023]
Abstract
The matrix pencil method (MPM) is explored for stable, reproducible data processing in nuclear magnetic resonance (NMR) relaxometry. Data from one-dimensional and two-dimensional relaxometry experiments designed to measure transverse relaxation T2, longitudinal relaxation T1, diffusion coefficient D values, and their correlations in a standard olive oil/water mixture serve as a platform available to any NMR spectroscopist to compare the performance of the MPM to the benchmark inverse Laplace transform (ILT). The data from two practical examples, including the drying of a solvent polymer system and the enzymatic digestion of polysialic acid, were also explored with the MPM and ILT. In the cases considered here, the MPM appears to outperform the ILT in terms of resolution and stability in the determination of fundamental constants for complex materials and mixtures.
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Affiliation(s)
- S N Fricke
- Department of Chemistry, 69 Chemistry Building, University of California, Davis, CA 95616, USA
| | - J D Seymour
- Department of Chemical and Biological Engineering, 306 Cobleigh Hall, Montana State University, Bozeman, MT 59717, USA
| | - M D Battistel
- Laboratory of Bacterial Polysaccharides, Center for Biologics Evaluation and Research, United States Food and Drug Administration, 10903 New Hampshire Ave., Silver Spring, MD 20993, USA
| | - D I Freedberg
- Laboratory of Bacterial Polysaccharides, Center for Biologics Evaluation and Research, United States Food and Drug Administration, 10903 New Hampshire Ave., Silver Spring, MD 20993, USA
| | - C D Eads
- The Procter & Gamble Company, 8700 S. Mason-Montgomery Road, Mason, OH 45040, USA
| | - M P Augustine
- Department of Chemistry, 69 Chemistry Building, University of California, Davis, CA 95616, USA.
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11
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Pas K, Komlosh ME, Perl DP, Basser PJ, Benjamini D. Retaining information from multidimensional correlation MRI using a spectral regions of interest generator. Sci Rep 2020; 10:3246. [PMID: 32094400 PMCID: PMC7040019 DOI: 10.1038/s41598-020-60092-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Accepted: 02/07/2020] [Indexed: 11/09/2022] Open
Abstract
Multidimensional correlation magnetic resonance imaging (MRI) is an emerging imaging modality that is capable of disentangling highly heterogeneous and opaque systems according to chemical and physical interactions of water within them. Using this approach, the conventional three dimensional MR scalar images are replaced with spatially resolved multidimensional spectra. The ensuing abundance in microstructural and chemical information is a blessing that incorporates a real challenge: how does one distill and refine it into images while retaining its significant components? In this paper we introduce a general framework that preserves the spectral information from spatially resolved multidimensional data. Equal weight is given to significant spectral components at the single voxel level, resulting in a summarized image spectrum. This spectrum is then used to define spectral regions of interest that are utilized to reconstruct images of sub-voxel components. Using numerical simulations we first show that, contrary to the conventional approach, the proposed framework preserves spectral resolution, and in turn, sensitivity and specificity of the reconstructed images. The retained spectral resolution allows, for the first time, to observe an array of distinct [Formula: see text]-[Formula: see text]-[Formula: see text] components images of the human brain. The robustly generated images of sub-voxel components overcome the limited spatial resolution of MRI, thus advancing multidimensional correlation MRI to fulfilling its full potential.
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Affiliation(s)
- Kristofor Pas
- National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20817, USA
- The Department of Biomedical Engineering, University of Texas at Arlington, Arlington, TX, 76010, USA
| | - Michal E Komlosh
- The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, 20817, USA
- The Center for Neuroscience and Regenerative Medicine, Uniformed Service University of the Health Sciences, Bethesda, MD, 20814, USA
| | - Daniel P Perl
- The Center for Neuroscience and Regenerative Medicine, Uniformed Service University of the Health Sciences, Bethesda, MD, 20814, USA
| | - Peter J Basser
- The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, 20817, USA
| | - Dan Benjamini
- The Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, 20817, USA.
- The Center for Neuroscience and Regenerative Medicine, Uniformed Service University of the Health Sciences, Bethesda, MD, 20814, USA.
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12
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Tullo S, Patel R, Devenyi GA, Salaciak A, Bedford SA, Farzin S, Wlodarski N, Tardif CL, Breitner JCS, Chakravarty MM. MR-based age-related effects on the striatum, globus pallidus, and thalamus in healthy individuals across the adult lifespan. Hum Brain Mapp 2019; 40:5269-5288. [PMID: 31452289 PMCID: PMC6864890 DOI: 10.1002/hbm.24771] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 07/17/2019] [Accepted: 08/05/2019] [Indexed: 01/18/2023] Open
Abstract
While numerous studies have used magnetic resonance imaging (MRI) to elucidate normative age-related trajectories in subcortical structures across the human lifespan, there exists substantial heterogeneity among different studies. Here, we investigated the normative relationships between age and morphology (i.e., volume and shape), and microstructure (using the T1-weighted/T2-weighted [T1w/T2w] signal ratio as a putative index of myelin and microstructure) of the striatum, globus pallidus, and thalamus across the adult lifespan using a dataset carefully quality controlled, yielding a final sample of 178 for the morphological analyses, and 162 for the T1w/T2w analyses from an initial dataset of 253 healthy subjects, aged 18-83. In accordance with previous cross-sectional studies of adults, we observed age-related volume decrease that followed a quadratic relationship between age and bilateral striatal and thalamic volumes, and a linear relationship in the globus pallidus. Our shape indices consistently demonstrated age-related posterior and medial areal contraction bilaterally across all three structures. Beyond morphology, we observed a quadratic inverted U-shaped relationship between T1w/T2w signal ratio and age, with a peak value occurring in middle age (at around 50 years old). After permutation testing, the Akaike information criterion determined age relationships remained significant for the bilateral globus pallidus and thalamus, for both the volumetric and T1w/T2w analyses. Our findings serve to strengthen and expand upon previous volumetric analyses by providing a normative baseline of morphology and microstructure of these structures to which future studies investigating patients with various disorders can be compared.
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Affiliation(s)
- Stephanie Tullo
- Integrated Program in NeuroscienceMcGill UniversityMontrealQuebecCanada
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
| | - Raihaan Patel
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
- Department of Biological and Biomedical EngineeringMcGill UniversityMontrealQuebecCanada
| | - Gabriel A. Devenyi
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
- Department of PsychiatryMcGill UniversityMontrealQuebecCanada
| | - Alyssa Salaciak
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
| | - Saashi A. Bedford
- Integrated Program in NeuroscienceMcGill UniversityMontrealQuebecCanada
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
| | - Sarah Farzin
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
| | - Nancy Wlodarski
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
| | - Christine L. Tardif
- McConnell Brain Imaging CenterMontreal Neurological Institute, McGill UniversityMontrealQuebecCanada
| | | | - John C. S. Breitner
- Centre for the Studies on the Prevention of ADDouglas Mental Health University InstituteVerdunQuebecCanada
| | - M. Mallar Chakravarty
- Integrated Program in NeuroscienceMcGill UniversityMontrealQuebecCanada
- Computational Brain Anatomy Laboratory, Cerebral Imaging CentreDouglas Mental Health University InstituteVerdunQuebecCanada
- Department of Biological and Biomedical EngineeringMcGill UniversityMontrealQuebecCanada
- Department of PsychiatryMcGill UniversityMontrealQuebecCanada
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13
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Schmidbauer V, Geisl G, Diogo M, Weber M, Goeral K, Klebermass-Schrehof K, Berger A, Prayer D, Kasprian G. SyMRI detects delayed myelination in preterm neonates. Eur Radiol 2019; 29:7063-7072. [PMID: 31286188 PMCID: PMC6828642 DOI: 10.1007/s00330-019-06325-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 05/28/2019] [Accepted: 06/12/2019] [Indexed: 12/16/2022]
Abstract
OBJECTIVES The software "SyMRI" generates different MR contrasts and characterizes tissue properties based on a single acquisition of a multi-dynamic multi-echo (MDME)-FLAIR sequence. The aim of this study was to assess the applicability of "SyMRI" in the assessment of myelination in preterm and term-born neonates. Furthermore, "SyMRI" was compared with conventional MRI. METHODS A total of 30 preterm and term-born neonates were examined at term-equivalent age using a standardized MRI protocol. MDME sequence (acquisition time, 5 min, 24 s)-based post-processing was performed using "SyMRI". Myelination was assessed by scoring seven brain regions on quantitative T1-/T2-maps, generated by "SyMRI" and on standard T1-/T2-weighted images, acquired separately. Analysis of covariance (ANCOVA) (covariate, gestational age (GA) at MRI (GAMRI)) was used for group comparison. RESULTS In 25/30 patients (83.3%) (18 preterm and seven term-born neonates), "SyMRI" acquisitions were successfully performed. "SyMRI"-based myelination scores were significantly lower in preterm compared with term-born neonates (ANCOVA: T1: F(1, 22) = 7.420, p = 0.012; T2: F(1, 22) = 5.658, p = 0.026). "SyMRI"-based myelination scores positively correlated with GAMRI (T1: r = 0.662, n = 25, p ≤ 0.001; T2: r = 0.676, n = 25, p ≤ 0.001). The myelination scores based on standard MRI did not correlate with the GAMRI. No significant differences between preterm and term-born neonates were detectable. CONCLUSIONS "SyMRI" is a highly promising MR technique for neonatal brain imaging. "SyMRI" is superior to conventional MR sequences in the visual detection of delayed myelination in preterm neonates. KEY POINTS • By providing multiple MR contrasts, "SyMRI" is a time-saving method in neonatal brain imaging. • Differences concerning the myelination in term-born and preterm infants are visually detectable on T1-/T2-weighted maps generated by "SyMRI". • "SyMRI" allows a faster and more sensitive assessment of myelination compared with standard MR sequences.
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Affiliation(s)
- Victor Schmidbauer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Gudrun Geisl
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Mariana Diogo
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Michael Weber
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Katharina Goeral
- Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Katrin Klebermass-Schrehof
- Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Angelika Berger
- Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Daniela Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Gregor Kasprian
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
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14
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Lampinen B, Szczepankiewicz F, Novén M, van Westen D, Hansson O, Englund E, Mårtensson J, Westin C, Nilsson M. Searching for the neurite density with diffusion MRI: Challenges for biophysical modeling. Hum Brain Mapp 2019; 40:2529-2545. [PMID: 30802367 PMCID: PMC6503974 DOI: 10.1002/hbm.24542] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 01/17/2019] [Accepted: 02/03/2019] [Indexed: 12/19/2022] Open
Abstract
In vivo mapping of the neurite density with diffusion MRI (dMRI) is a high but challenging aim. First, it is unknown whether all neurites exhibit completely anisotropic ("stick-like") diffusion. Second, the "density" of tissue components may be confounded by non-diffusion properties such as T2 relaxation. Third, the domain of validity for the estimated parameters to serve as indices of neurite density is incompletely explored. We investigated these challenges by acquiring data with "b-tensor encoding" and multiple echo times in brain regions with low orientation coherence and in white matter lesions. Results showed that microscopic anisotropy from b-tensor data is associated with myelinated axons but not with dendrites. Furthermore, b-tensor data together with data acquired for multiple echo times showed that unbiased density estimates in white matter lesions require data-driven estimates of compartment-specific T2 values. Finally, the "stick" fractions of different biophysical models could generally not serve as neurite density indices across the healthy brain and white matter lesions, where outcomes of comparisons depended on the choice of constraints. In particular, constraining compartment-specific T2 values was ambiguous in the healthy brain and had a large impact on estimated values. In summary, estimating neurite density generally requires accounting for different diffusion and/or T2 properties between axons and dendrites. Constrained "index" parameters could be valid within limited domains that should be delineated by future studies.
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Affiliation(s)
- Björn Lampinen
- Clinical Sciences Lund, Medical Radiation PhysicsLund UniversityLundSweden
| | - Filip Szczepankiewicz
- Clinical Sciences Lund, Medical Radiation PhysicsLund UniversityLundSweden
- Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUS
| | - Mikael Novén
- Centre for Languages and LiteratureLund UniversityLundSweden
| | | | - Oskar Hansson
- Clinical Sciences Malmö, Clinical Memory Research UnitLund UniversityLundSweden
| | - Elisabet Englund
- Clinical Sciences Lund, Oncology and PathologyLund UniversityLundSweden
| | - Johan Mårtensson
- Clinical Sciences Lund, Department of Logopedics, Phoniatrics and AudiologyLund UniversityLundSweden
| | | | - Markus Nilsson
- Clinical Sciences Lund, RadiologyLund UniversityLundSweden
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15
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McLachlan K, Vavasour I, MacKay A, Brain U, Oberlander T, Loock C, Reynolds JN, Beaulieu C. Myelin Water Fraction Imaging of the Brain in Children with Prenatal Alcohol Exposure. Alcohol Clin Exp Res 2019; 43:833-841. [PMID: 30889291 DOI: 10.1111/acer.14024] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 03/10/2019] [Indexed: 01/20/2023]
Abstract
BACKGROUND Prenatal alcohol exposure (PAE) is linked to alterations of cerebral white matter, including volume and nonspecific diffusion magnetic resonance imaging (MRI) indices of microstructure in humans. Some animal models of PAE have demonstrated myelination deficiencies, but myelin levels have not yet been evaluated in individuals with PAE. Multiecho T2 MRI offers a quantitative method to estimate myelin water fraction (MWF; related to myelin content) noninvasively, which was used here to evaluate brain myelination in children with PAE. METHODS Participants with PAE (n = 10, 6 females, mean age 13.9 years, range 7 to 18 years) and controls (n = 14, 11 females, mean age 13.2 years, range 9 to 16 years) underwent 3T MRI of the brain. T2 images (15 minutes acquisition for 32 echoes) were used to create MWF maps from which mean MWF was measured in 12 regions of interest (ROIs) including 8 in white matter and 4 in deep gray matter. RESULTS As expected, across the combined sample, MWF was highest for major white matter tracts such as the internal capsule and genu/splenium of the corpus callosum (10 to 18%) while the caudate and putamen had MWF less than 5%. Mean MWF was similar across 11/12 brain white and gray matter regions for the PAE and control groups (L/R internal capsule, major forceps, putamen, caudate nucleus, L minor forceps, genu and splenium of corpus callosum). In the PAE group, MWF was positively correlated with age in the genu of corpus callosum and right minor forceps, notably 2 frontal tracts. CONCLUSIONS Given comparable MRI-derived myelination fraction measures in PAE relative to controls, white matter alterations shown in other imaging studies, such as diffusion tensor imaging, may reflect microstructural anomalies related to axon caliber and density.
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Affiliation(s)
| | - Irene Vavasour
- Department of Radiology , University of British Columbia, Vancouver, BC, Canada
| | - Alex MacKay
- Department of Radiology , University of British Columbia, Vancouver, BC, Canada.,Department of Physics and Astronomy , University of British Columbia, Vancouver, BC, Canada
| | - Ursula Brain
- Department of Pediatrics , University of British Columbia, Vancouver, BC, Canada
| | - Tim Oberlander
- Department of Pediatrics , University of British Columbia, Vancouver, BC, Canada
| | - Christine Loock
- Department of Pediatrics , University of British Columbia, Vancouver, BC, Canada
| | - James N Reynolds
- Department of Biomedical and Molecular Sciences , Queens University, Kingston, ON, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering , University of Alberta, Edmonton, AB, Canada
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16
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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: 34] [Impact Index Per Article: 5.7] [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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17
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Veraart J, Novikov DS, Fieremans E. TE dependent Diffusion Imaging (TEdDI) distinguishes between compartmental T 2 relaxation times. Neuroimage 2018; 182:360-369. [PMID: 28935239 PMCID: PMC5858973 DOI: 10.1016/j.neuroimage.2017.09.030] [Citation(s) in RCA: 127] [Impact Index Per Article: 21.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2017] [Revised: 09/12/2017] [Accepted: 09/15/2017] [Indexed: 11/24/2022] Open
Abstract
Biophysical modeling of macroscopic diffusion-weighted MRI signal in terms of microscopic cellular parameters holds the promise of quantifying the integrity of white matter. Unfortunately, even fairly simple multi-compartment models of proton diffusion in the white matter do not provide a unique, biophysically plausible solution. Here we report a nontrivial diffusion MRI signal dependence on echo time (TE) in human white matter in vivo. We demonstrate that such TE dependence originates from compartment-specific T2 values and that it is a promising "orthogonal measure" able to break the degeneracy in parameter estimation, and to yield important relaxation metrics robustly. We thereby enable the precise estimation of the intra- and extra-axonal water T2 relaxation times, which is precluded by a limited signal-to-noise ratio when using multi-echo relaxometry alone.
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Affiliation(s)
- Jelle Veraart
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, NY, USA.
| | - Dmitry S Novikov
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, NY, USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, NY, USA
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18
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Spees WM, Lin TH, Sun P, Song C, George A, Gary SE, Yang HC, Song SK. MRI-based assessment of function and dysfunction in myelinated axons. Proc Natl Acad Sci U S A 2018; 115:E10225-E10234. [PMID: 30297414 PMCID: PMC6205472 DOI: 10.1073/pnas.1801788115] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Repetitive electrical activity produces microstructural alteration in myelinated axons, which may afford the opportunity to noninvasively monitor function of myelinated fibers in peripheral nervous system (PNS)/CNS pathways. Microstructural changes were assessed via two different magnetic-resonance-based approaches: diffusion fMRI and dynamic T2 spectroscopy in the ex vivo perfused bullfrog sciatic nerves. Using this robust, classical model as a platform for testing, we demonstrate that noninvasive diffusion fMRI, based on standard diffusion tensor imaging (DTI), can clearly localize the sites of axonal conduction blockage as might be encountered in neurotrauma or other lesion types. It is also shown that the diffusion fMRI response is graded in proportion to the total number of electrical impulses carried through a given locus. Dynamic T2 spectroscopy of the perfused frog nerves point to an electrical-activity-induced redistribution of tissue water and myelin structural changes. Diffusion basis spectrum imaging (DBSI) reveals a reversible shift of tissue water into a restricted isotropic diffusion signal component. Submyelinic vacuoles are observed in electron-microscopy images of tissue fixed during electrical stimulation. A slowing of the compound action potential conduction velocity accompanies repetitive electrical activity. Correlations between electrophysiology and MRI parameters during and immediately after stimulation are presented. Potential mechanisms and interpretations of these results are discussed.
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Affiliation(s)
- William M Spees
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110;
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110
| | - Tsen-Hsuan Lin
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Peng Sun
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Chunyu Song
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63110
| | - Ajit George
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Sam E Gary
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Hsin-Chieh Yang
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Sheng-Kwei Song
- Biomedical MR Laboratory, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63110
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19
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Ouyang M, Dubois J, Yu Q, Mukherjee P, Huang H. Delineation of early brain development from fetuses to infants with diffusion MRI and beyond. Neuroimage 2018; 185:836-850. [PMID: 29655938 DOI: 10.1016/j.neuroimage.2018.04.017] [Citation(s) in RCA: 135] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 04/01/2018] [Accepted: 04/08/2018] [Indexed: 02/08/2023] Open
Abstract
Dynamic macrostructural and microstructural changes take place from the mid-fetal stage to 2 years after birth. Delineating structural changes of the brain during early development provides new insights into the complicated processes of both typical development and the pathological mechanisms underlying various psychiatric and neurological disorders including autism, attention deficit hyperactivity disorder and schizophrenia. Decades of histological studies have identified strong spatial and functional maturation gradients in human brain gray and white matter. The recent improvements in magnetic resonance imaging (MRI) techniques, especially diffusion MRI (dMRI), relaxometry imaging, and magnetization transfer imaging (MTI) have provided unprecedented opportunities to non-invasively quantify and map the early developmental changes at whole brain and regional levels. Here, we review the recent advances in understanding early brain structural development during the second half of gestation and the first two postnatal years using modern MR techniques. Specifically, we review studies that delineate the emergence and microstructural maturation of white matter tracts, as well as dynamic mapping of inhomogeneous cortical microstructural organization unique to fetuses and infants. These imaging studies converge into maturational curves of MRI measurements that are distinctive across different white matter tracts and cortical regions. Furthermore, contemporary models offering biophysical interpretations of the dMRI-derived measurements are illustrated to infer the underlying microstructural changes. Collectively, this review summarizes findings that contribute to charting spatiotemporally heterogeneous gray and white matter structural development, offering MRI-based biomarkers of typical brain development and setting the stage for understanding aberrant brain development in neurodevelopmental disorders.
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Affiliation(s)
- Minhui Ouyang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States
| | - Jessica Dubois
- INSERM, UMR992, CEA, NeuroSpin Center, University Paris Saclay, Gif-sur-Yvette, France
| | - Qinlin Yu
- Radiology Research, Children's Hospital of Philadelphia, PA, United States
| | - Pratik Mukherjee
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, CA, United States
| | - Hao Huang
- Radiology Research, Children's Hospital of Philadelphia, PA, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, United States.
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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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21
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Knight MJ, Smith-Collins A, Newell S, Denbow M, Kauppinen RA. Cerebral White Matter Maturation Patterns in Preterm Infants: An MRI T2 Relaxation Anisotropy and Diffusion Tensor Imaging Study. J Neuroimaging 2017; 28:86-94. [PMID: 29205635 DOI: 10.1111/jon.12486] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Accepted: 11/01/2017] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND PURPOSE Preterm birth is associated with worse neurodevelopmental outcome, but brain maturation in preterm infants is poorly characterized with standard methods. We evaluated white matter (WM) of infant brains at term-equivalent age, as a function of gestational age at birth, using multimodal magnetic resonance imaging (MRI). METHODS Infants born very preterm (<32 weeks gestation) and late preterm (33-36 weeks gestation) were scanned at 3 T at term-equivalent age using diffusion tensor imaging (DTI) and T2 relaxometry. MRI data were analyzed using tract-based spatial statistics, and anisotropy of T2 relaxation was also determined. Principal component analysis and linear discriminant analysis were applied to seek the variables best distinguishing very preterm and late preterm groups. RESULTS Across widespread regions of WM, T2 is longer in very preterm infants than in late preterm ones. These effects are more prevalent in regions of WM that myelinate earlier and faster. Similar effects are obtained from DTI, showing that fractional anisotropy (FA) is lower and radial diffusivity higher in the very preterm group, with a bias toward earlier myelinating regions. Discriminant analysis shows high sensitivity and specificity of combined T2 relaxometry and DTI for the detection of a distinct WM development pathway in very preterm infants. T2 relaxation is anisotropic, depending on the angle between WM fiber and magnetic field, and this effect is modulated by FA. CONCLUSIONS Combined T2 relaxometry and DTI characterizes specific patterns of retarded WM maturation, at term equivalent age, in infants born very preterm relative to late preterm.
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Affiliation(s)
| | - Adam Smith-Collins
- Clinical Research and Imaging Centre, University of Bristol, UK.,Fetal Medicine Unit, St Michael's Hospital, University Hospitals Bristol NHS Foundation Trust, UK
| | - Sarah Newell
- Fetal Medicine Unit, St Michael's Hospital, University Hospitals Bristol NHS Foundation Trust, UK
| | - Mark Denbow
- Fetal Medicine Unit, St Michael's Hospital, University Hospitals Bristol NHS Foundation Trust, UK
| | - Risto A Kauppinen
- School of Experimental Psychology, University of Bristol, UK.,Clinical Research and Imaging Centre, University of Bristol, UK
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22
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Benjamini D, Basser PJ. Magnetic resonance microdynamic imaging reveals distinct tissue microenvironments. Neuroimage 2017; 163:183-196. [PMID: 28943412 DOI: 10.1016/j.neuroimage.2017.09.033] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2017] [Revised: 09/12/2017] [Accepted: 09/18/2017] [Indexed: 10/18/2022] Open
Abstract
Magnetic resonance imaging (MRI) provides a powerful set of tools with which to investigate biological tissues noninvasively and in vivo. Tissues are heterogeneous in nature; an imaging voxel contains an ensemble of different cells and extracellular matrix components. A long-standing challenge has been to infer the content of and interactions among these microscopic tissue components within a macroscopic imaging voxel. Spatially resolved multidimensional relaxation-diffusion correlation (REDCO) spectroscopy holds the potential to deliver such microdynamic information. However, to date, vast data requirements have mostly relegated these type of measurements to nuclear magnetic resonance applications and prevented them from being widely and successfully used in conjunction with imaging. By using a novel data acquisition and processing strategy in this study, spatially resolved REDCO could be performed in reasonable scanning times with excellent prospects for clinical applications. This new MR imaging framework-which we term "magnetic resonance microdynamic imaging (MRMI)"-permits the simultaneous noninvasive and model-free quantification of multiple subcellular, cellular, and interstitial tissue microenvironments within a voxel. MRMI is demonstrated with a fixed spinal cord specimen, enabling the quantification of microscopic tissue components with unprecedented specificity. Tissue components, such as axons, neuronal and glial soma, and myelin were identified on the basis of their multispectral signature within individual imaging voxels. These tissue elements could then be composed into images and be correlated with immunohistochemistry findings. MRMI provides novel image contrasts of tissue components and a new family of microdynamic biomarkers that could lead to new diagnostic imaging approaches to probe biological tissue alterations accompanied by pathological or developmental changes.
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Affiliation(s)
- Dan Benjamini
- Section on Quantitative Imaging and Tissue Sciences, NICHD, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Peter J Basser
- Section on Quantitative Imaging and Tissue Sciences, NICHD, National Institutes of Health, Bethesda, MD 20892, USA
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23
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Cronin MJ, Wang N, Decker KS, Wei H, Zhu WZ, Liu C. Exploring the origins of echo-time-dependent quantitative susceptibility mapping (QSM) measurements in healthy tissue and cerebral microbleeds. Neuroimage 2017; 149:98-113. [PMID: 28126551 DOI: 10.1016/j.neuroimage.2017.01.053] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Revised: 01/19/2017] [Accepted: 01/22/2017] [Indexed: 12/20/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) is increasingly used to measure variation in tissue composition both in the brain and in other areas of the body in a range of disease pathologies. Although QSM measurements were originally believed to be independent of the echo time (TE) used in the gradient-recalled echo (GRE) acquisition from which they are derived; recent literature (Sood et al., 2016) has shown that these measurements can be highly TE-dependent in a number of brain regions. In this work we systematically investigate possible causes of this effect through analysis of apparent frequency and QSM measurements derived from data acquired at multiple TEs in vivo in healthy brain regions and in cerebral microbleeds (CMBs); QSM data acquired in a gadolinium-doped phantom; and in QSM data derived from idealized simulated phase data. Apparent frequency measurements in the optic radiations (OR) and central corpus callosum (CC) were compared to those predicted by a 3-pool white matter model, however the model failed to fully explain contrasting frequency profiles measured in the OR and CC. Our results show that TE-dependent QSM measurements can be caused by a failure of phase unwrapping algorithms in and around strong susceptibility sources such as CMBs; however, in healthy brain regions this behavior appears to result from intrinsic non-linear phase evolution in the MR signal. From these results we conclude that care must be taken when deriving frequency and QSM measurements in strong susceptibility sources due to the inherent limitations in phase unwrapping; and that while signal compartmentalization due to tissue microstructure and content is a plausible cause of TE-dependent frequency and QSM measurements in healthy brain regions, better sampling of the MR signal and more complex models of tissue are needed to fully exploit this relationship.
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Affiliation(s)
- Matthew J Cronin
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA; Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA
| | - Nian Wang
- Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA
| | - Kyle S Decker
- Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA
| | - Hongjiang Wei
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA; Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA
| | - Wen-Zhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA; Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA.
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24
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High-Resolution Axonal Bundle (Fascicle) Assessment and Triple-Echo Steady-State T2 Mapping of the Median Nerve at 7 T. Invest Radiol 2016; 51:529-35. [DOI: 10.1097/rli.0000000000000265] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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25
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Jelescu IO, Veraart J, Fieremans E, Novikov DS. Degeneracy in model parameter estimation for multi-compartmental diffusion in neuronal tissue. NMR IN BIOMEDICINE 2016; 29:33-47. [PMID: 26615981 PMCID: PMC4920129 DOI: 10.1002/nbm.3450] [Citation(s) in RCA: 188] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2015] [Revised: 10/28/2015] [Accepted: 10/30/2015] [Indexed: 05/05/2023]
Abstract
The ultimate promise of diffusion MRI (dMRI) models is specificity to neuronal microstructure, which may lead to distinct clinical biomarkers using noninvasive imaging. While multi-compartment models are a common approach to interpret water diffusion in the brain in vivo, the estimation of their parameters from the dMRI signal remains an unresolved problem. Practically, even when q space is highly oversampled, nonlinear fit outputs suffer from heavy bias and poor precision. So far, this has been alleviated by fixing some of the model parameters to a priori values, for improved precision at the expense of accuracy. Here we use a representative two-compartment model to show that fitting fails to determine the five model parameters from over 60 measurement points. For the first time, we identify the reasons for this poor performance. The first reason is the existence of two local minima in the parameter space for the objective function of the fitting procedure. These minima correspond to qualitatively different sets of parameters, yet they both lie within biophysically plausible ranges. We show that, at realistic signal-to-noise ratio values, choosing between the two minima based on the associated objective function values is essentially impossible. Second, there is an ensemble of very low objective function values around each of these minima in the form of a pipe. The existence of such a direction in parameter space, along which the objective function profile is very flat, explains the bias and large uncertainty in parameter estimation, and the spurious parameter correlations: in the presence of noise, the minimum can be randomly displaced by a very large amount along each pipe. Our results suggest that the biophysical interpretation of dMRI model parameters crucially depends on establishing which of the minima is closer to the biophysical reality and the size of the uncertainty associated with each parameter.
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Affiliation(s)
- Ileana O. Jelescu
- Correspondence to: I.O. Jelescu, Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA.
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Van Beek L, Vanderauwera J, Ghesquière P, Lagae L, De Smedt B. Longitudinal changes in mathematical abilities and white matter following paediatric mild traumatic brain injury. Brain Inj 2015; 29:1701-10. [DOI: 10.3109/02699052.2015.1075172] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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27
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Duval T, McNab JA, Setsompop K, Witzel T, Schneider T, Huang SY, Keil B, Klawiter EC, Wald LL, Cohen-Adad J. In vivo mapping of human spinal cord microstructure at 300mT/m. Neuroimage 2015; 118:494-507. [PMID: 26095093 DOI: 10.1016/j.neuroimage.2015.06.038] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Revised: 05/27/2015] [Accepted: 06/11/2015] [Indexed: 11/19/2022] Open
Abstract
The ability to characterize white matter microstructure non-invasively has important applications for the diagnosis and follow-up of several neurological diseases. There exists a family of diffusion MRI techniques, such as AxCaliber, that provide indices of axon microstructure, such as axon diameter and density. However, to obtain accurate measurements of axons with small diameters (<5μm), these techniques require strong gradients, i.e. an order of magnitude higher than the 40-80mT/m currently available in clinical systems. In this study we acquired AxCaliber diffusion data at a variety of different q-values and diffusion times in the spinal cord of five healthy subjects using a 300mT/m whole body gradient system. Acquisition and processing were optimized using state-of-the-art methods (e.g., 64-channel coil, template-based analysis). Results consistently show an average axon diameter of 4.5+/-1.1μm in the spinal cord white matter. Diameters ranged from 3.0μm (gracilis) to 5.9μm (spinocerebellar tracts). Values were similar across laterality (left-right), but statistically different across spinal cord pathways (p<10(-5)). The observed trends are similar to those observed in animal histology. This study shows, for the first time, in vivo mapping of axon diameter in the spinal cord at 300mT/m, thus creating opportunities for applications in spinal cord diseases.
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Affiliation(s)
- Tanguy Duval
- Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Jennifer A McNab
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Kawin Setsompop
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - Thomas Witzel
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - Torben Schneider
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Institute of Neurology, London, London, United Kingdom
| | - Susie Yi Huang
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - Boris Keil
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - Eric C Klawiter
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Lawrence L Wald
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
| | - Julien Cohen-Adad
- Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada.
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28
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Deoni SCL, Zinkstok JR, Daly E, Ecker C, Williams SCR, Murphy DGM. White-matter relaxation time and myelin water fraction differences in young adults with autism. Psychol Med 2015; 45:795-805. [PMID: 25111948 DOI: 10.1017/s0033291714001858] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Increasing evidence suggests that autism is associated with abnormal white-matter (WM) anatomy and impaired brain 'connectivity'. While myelin plays a critical role in synchronized brain communication, its aetiological role in autistic symptoms has only been indirectly addressed by WM volumetric, relaxometry and diffusion tensor imaging studies. A potentially more specific measure of myelin content, termed myelin water fraction (MWF), could provide improved sensitivity to myelin alteration in autism. METHOD We performed a cross-sectional imaging study that compared 14 individuals with autism and 14 age- and IQ-matched controls. T 1 relaxation times (T 1), T 2 relaxation times (T 2) and MWF values were compared between autistic subjects, diagnosed using the Autism Diagnostic Interview - Revised (ADI-R), with current symptoms assessed using the Autism Diagnostic Observation Schedule (ADOS) and typical healthy controls. Correlations between T 1, T 2 and MWF values with clinical measures [ADI-R, ADOS, and the Autism Quotient (AQ)] were also assessed. RESULTS Individuals with autism showed widespread WM T 1 and MWF differences compared to typical controls. Within autistic individuals, worse current social interaction skill as measured by the ADOS was related to reduced MWF although not T 1. No significant differences or correlations with symptoms were observed with respect to T 2. CONCLUSIONS Autistic individuals have significantly lower global MWF and higher T 1, suggesting widespread alteration in tissue microstructure and biochemistry. Areas of difference, including thalamic projections, cerebellum and cingulum, have previously been implicated in the disorder; however, this is the first study to specifically indicate myelin alteration in these regions.
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Affiliation(s)
- S C L Deoni
- Advanced Baby Imaging Laboratory,School of Engineering, Brown University,Providence, RI,USA
| | - J R Zinkstok
- Department of Forensic and Neurodevelopmental Sciences,Institute of Psychiatry, King's College London,London,UK
| | - E Daly
- Department of Forensic and Neurodevelopmental Sciences,Institute of Psychiatry, King's College London,London,UK
| | - C Ecker
- Department of Forensic and Neurodevelopmental Sciences,Institute of Psychiatry, King's College London,London,UK
| | - S C R Williams
- Department of Neuroimaging,Institute of Psychiatry, King's College London,London,UK
| | - D G M Murphy
- Department of Forensic and Neurodevelopmental Sciences,Institute of Psychiatry, King's College London,London,UK
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Ganzetti M, Wenderoth N, Mantini D. Whole brain myelin mapping using T1- and T2-weighted MR imaging data. Front Hum Neurosci 2014; 8:671. [PMID: 25228871 PMCID: PMC4151508 DOI: 10.3389/fnhum.2014.00671] [Citation(s) in RCA: 135] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2014] [Accepted: 08/12/2014] [Indexed: 11/13/2022] Open
Abstract
Despite recent advancements in MR imaging, non-invasive mapping of myelin in the brain still remains an open issue. Here we attempted to provide a potential solution. Specifically, we developed a processing workflow based on T1-w and T2-w MR data to generate an optimized myelin enhanced contrast image. The workflow allows whole brain mapping using the T1-w/T2-w technique, which was originally introduced as a non-invasive method for assessing cortical myelin content. The hallmark of our approach is a retrospective calibration algorithm, applied to bias-corrected T1-w and T2-w images, that relies on image intensities outside the brain. This permits standardizing the intensity histogram of the ratio image, thereby allowing for across-subject statistical analyses. Quantitative comparisons of image histograms within and across different datasets confirmed the effectiveness of our normalization procedure. Not only did the calibrated T1-w/T2-w images exhibit a comparable intensity range, but also the shape of the intensity histograms was largely corresponding. We also assessed the reliability and specificity of the ratio image compared to other MR-based techniques, such as magnetization transfer ratio (MTR), fractional anisotropy (FA), and fluid-attenuated inversion recovery (FLAIR). With respect to these other techniques, T1-w/T2-w had consistently high values, as well as low inter-subject variability, in brain structures where myelin is most abundant. Overall, our results suggested that the T1-w/T2-w technique may be a valid tool supporting the non-invasive mapping of myelin in the brain. Therefore, it might find important applications in the study of brain development, aging and disease.
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Affiliation(s)
- Marco Ganzetti
- Neural Control of Movement Laboratory, Department of Heath Sciences and Technology, ETH Zurich Zurich, Switzerland ; Department of Experimental Psychology, University of Oxford Oxford, UK
| | - Nicole Wenderoth
- Neural Control of Movement Laboratory, Department of Heath Sciences and Technology, ETH Zurich Zurich, Switzerland ; Laboratory of Movement Control and Neuroplasticity, Department of Kinesiology, KU Leuven Leuven, Belgium
| | - Dante Mantini
- Neural Control of Movement Laboratory, Department of Heath Sciences and Technology, ETH Zurich Zurich, Switzerland ; Department of Experimental Psychology, University of Oxford Oxford, UK
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Dubois J, Dehaene-Lambertz G, Kulikova S, Poupon C, Hüppi PS, Hertz-Pannier L. The early development of brain white matter: A review of imaging studies in fetuses, newborns and infants. Neuroscience 2014; 276:48-71. [PMID: 24378955 DOI: 10.1016/j.neuroscience.2013.12.044] [Citation(s) in RCA: 494] [Impact Index Per Article: 49.4] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2013] [Revised: 12/12/2013] [Accepted: 12/16/2013] [Indexed: 12/13/2022]
Affiliation(s)
- J Dubois
- INSERM, U992, Cognitive Neuroimaging Unit, Gif-sur-Yvette, France; CEA, NeuroSpin Center, UNICOG, Gif-sur-Yvette, France; University Paris Sud, Orsay, France.
| | - G Dehaene-Lambertz
- INSERM, U992, Cognitive Neuroimaging Unit, Gif-sur-Yvette, France; CEA, NeuroSpin Center, UNICOG, Gif-sur-Yvette, France; University Paris Sud, Orsay, France
| | - S Kulikova
- CEA, NeuroSpin Center, UNIACT, Gif-sur-Yvette, France; INSERM, U663, Child epilepsies and brain plasticity, Paris, France; University Paris Descartes, Paris, France
| | - C Poupon
- CEA, NeuroSpin Center, UNIRS, Gif-sur-Yvette, France
| | - P S Hüppi
- Geneva University Hospitals, Department of Pediatrics, Division of Development and Growth, Geneva, Switzerland; Harvard Medical School, Children's Hospital, Department of Neurology, Boston, MA, USA
| | - L Hertz-Pannier
- CEA, NeuroSpin Center, UNIACT, Gif-sur-Yvette, France; INSERM, U663, Child epilepsies and brain plasticity, Paris, France; University Paris Descartes, Paris, France
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31
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Miller TR, Mohan S, Choudhri AF, Gandhi D, Jindal G. Advances in multiple sclerosis and its variants: conventional and newer imaging techniques. Radiol Clin North Am 2014; 52:321-36. [PMID: 24582342 DOI: 10.1016/j.rcl.2013.11.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Multiple sclerosis (MS) and its variants are inflammatory as well as neurodegenerative diseases that diffusely affect the central nervous system (CNS). There is a poor correlation between traditional imaging findings and symptoms in patients with MS. Current research in conventional magnetic resonance (MR) imaging of MS and related diseases includes optimization of hardware and pulse sequences and the development of automated and semiautomated techniques to measure and quantify disease burden. Advanced nonconventional MR techniques such as diffusion tensor and functional MR imaging probe the changes found in the CNS, and correlate these findings with clinical measures of disease.
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Affiliation(s)
- Timothy R Miller
- Neuroradiology Division, Department of Radiology, University of Maryland Medical Center, Baltimore, MD 21201, USA.
| | - Suyash Mohan
- Neuroradiology Division, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Asim F Choudhri
- Neuroradiology Division, Department of Radiology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Dheeraj Gandhi
- Neuroradiology Division, Department of Radiology, University of Maryland Medical Center, Baltimore, MD 21201, USA
| | - Gaurav Jindal
- Neuroradiology Division, Department of Radiology, University of Maryland Medical Center, Baltimore, MD 21201, USA
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Irrechukwu ON, Von Thaer S, Frank EH, Lin PC, Reiter DA, Grodzinsky AJ, Spencer RG. Prediction of cartilage compressive modulus using multiexponential analysis of T(2) relaxation data and support vector regression. NMR IN BIOMEDICINE 2014; 27:468-77. [PMID: 24519878 PMCID: PMC4608539 DOI: 10.1002/nbm.3083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2013] [Revised: 12/04/2013] [Accepted: 01/07/2014] [Indexed: 05/14/2023]
Abstract
Evaluation of mechanical characteristics of cartilage by magnetic resonance imaging would provide a noninvasive measure of tissue quality both for tissue engineering and when monitoring clinical response to therapeutic interventions for cartilage degradation. We use results from multiexponential transverse relaxation analysis to predict equilibrium and dynamic stiffness of control and degraded bovine nasal cartilage, a biochemical model for articular cartilage. Sulfated glycosaminoglycan concentration/wet weight (ww) and equilibrium and dynamic stiffness decreased with degradation from 103.6 ± 37.0 µg/mg ww, 1.71 ± 1.10 MPa and 15.3 ± 6.7 MPa in controls to 8.25 ± 2.4 µg/mg ww, 0.015 ± 0.006 MPa and 0.89 ± 0.25MPa, respectively, in severely degraded explants. Magnetic resonance measurements were performed on cartilage explants at 4 °C in a 9.4 T wide-bore NMR spectrometer using a Carr-Purcell-Meiboom-Gill sequence. Multiexponential T2 analysis revealed four water compartments with T2 values of approximately 0.14, 3, 40 and 150 ms, with corresponding weight fractions of approximately 3, 2, 4 and 91%. Correlations between weight fractions and stiffness based on conventional univariate and multiple linear regressions exhibited a maximum r(2) of 0.65, while those based on support vector regression (SVR) had a maximum r(2) value of 0.90. These results indicate that (i) compartment weight fractions derived from multiexponential analysis reflect cartilage stiffness and (ii) SVR-based multivariate regression exhibits greatly improved accuracy in predicting mechanical properties as compared with conventional regression.
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Affiliation(s)
- Onyi N. Irrechukwu
- National Institute on Aging, National Institutes of Health, Baltimore MD 21224
| | - Sarah Von Thaer
- National Institute on Aging, National Institutes of Health, Baltimore MD 21224
| | - Eliot H. Frank
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Ping-Chang Lin
- National Institute on Aging, National Institutes of Health, Baltimore MD 21224
| | - David A. Reiter
- National Institute on Aging, National Institutes of Health, Baltimore MD 21224
| | - Alan J. Grodzinsky
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Richard G. Spencer
- National Institute on Aging, National Institutes of Health, Baltimore MD 21224
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Tusor N, Arichi T, Counsell SJ, Edwards AD. Brain development in preterm infants assessed using advanced MRI techniques. Clin Perinatol 2014; 41:25-45. [PMID: 24524445 DOI: 10.1016/j.clp.2013.10.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Infants who are born preterm have a high incidence of neurocognitive and neurobehavioral abnormalities, which may be associated with impaired brain development. Advanced magnetic resonance imaging (MRI) approaches, such as diffusion MRI (d-MRI) and functional MRI (fMRI), provide objective and reproducible measures of brain development. Indices derived from d-MRI can be used to provide quantitative measures of preterm brain injury. Although fMRI of the neonatal brain is currently a research tool, future studies combining d-MRI and fMRI have the potential to assess the structural and functional properties of the developing brain and its response to injury.
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Affiliation(s)
- Nora Tusor
- Centre for the Developing Brain, Department of Perinatal Imaging, St Thomas' Hospital, King's College London, Westminster Bridge Road, London SE1 7EH, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, Department of Perinatal Imaging, St Thomas' Hospital, King's College London, Westminster Bridge Road, London SE1 7EH, UK; Department of Bioengineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Serena J Counsell
- Centre for the Developing Brain, Department of Perinatal Imaging, St Thomas' Hospital, King's College London, Westminster Bridge Road, London SE1 7EH, UK
| | - A David Edwards
- Centre for the Developing Brain, Department of Perinatal Imaging, St Thomas' Hospital, King's College London, Westminster Bridge Road, London SE1 7EH, UK; Department of Bioengineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
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Samson RS, Cardoso MJ, Muhlert N, Sethi V, Wheeler-Kingshott CA, Ron M, Ourselin S, Miller DH, Chard DT. Investigation of outer cortical magnetisation transfer ratio abnormalities in multiple sclerosis clinical subgroups. Mult Scler 2014; 20:1322-30. [PMID: 24552746 DOI: 10.1177/1352458514522537] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
BACKGROUND Pathological abnormalities including demyelination and neuronal loss are reported in the outer cortex in multiple sclerosis (MS). OBJECTIVE We investigated for in vivo evidence of outer cortical abnormalities by measuring the magnetisation transfer ratio (MTR) in MS patients of different subgroups. METHODS Forty-four relapsing-remitting (RR) (mean age 41.9 years, median Expanded Disability Status Scale (EDSS) 2.0), 25 secondary progressive (SP) (54.1 years, EDSS 6.5) and 19 primary progressive (PP) (53.1 years, EDSS 6.0) MS patients and 35 healthy control subjects (mean age 39.2 years) were studied. Three-dimensional (3D) 1×1×1mm(3) T1-weighted images and MTR data were acquired. The cortex was segmented, then subdivided into outer and inner bands, and MTR values were calculated for each band. RESULTS In a pairwise analysis, mean outer cortical MTR was lower than mean inner cortical MTR in all MS groups and controls (p<0.001). Compared with controls, outer cortical MTR was decreased in SPMS (p<0.001) and RRMS (p<0.01), but not PPMS. Outer cortical MTR was lower in SPMS than PPMS (p<0.01) and RRMS (p<0.01). CONCLUSIONS Lower outer than inner cortical MTR in healthy controls may reflect differences in myelin content. The lowest outer cortical MTR was seen in SPMS and is consistent with more extensive outer cortical (including subpial) pathology, such as demyelination and neuronal loss, as observed in post-mortem studies of SPMS patients.
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Affiliation(s)
| | - Manuel J Cardoso
- Centre for Medical Image Computing, Department of Computer Sciences, University College London, UK Dementia Research Centre, Department of Neurodegenerative Diseases, Institute of Neurology, University College London, UK
| | - Nils Muhlert
- NMR Research Unit, UCL Institute of Neurology, London, UK
| | - Varun Sethi
- NMR Research Unit, UCL Institute of Neurology, London, UK
| | | | - Maria Ron
- NMR Research Unit, UCL Institute of Neurology, London, UK
| | - Sebastian Ourselin
- Centre for Medical Image Computing, Department of Computer Sciences, University College London, UK Dementia Research Centre, Department of Neurodegenerative Diseases, Institute of Neurology, University College London, UK
| | - David H Miller
- NMR Research Unit, UCL Institute of Neurology, London, UK
| | - Declan T Chard
- NMR Research Unit, UCL Institute of Neurology, London, UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, UK
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35
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Oishi K, Faria AV, Yoshida S, Chang L, Mori S. Reprint of "Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging". Int J Dev Neurosci 2014; 32:28-40. [PMID: 24295553 PMCID: PMC4696018 DOI: 10.1016/j.ijdevneu.2013.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2012] [Revised: 05/24/2013] [Accepted: 06/13/2013] [Indexed: 01/18/2023] Open
Abstract
The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a "growth percentile chart," which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application.
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Affiliation(s)
- Kenichi Oishi
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Andreia V Faria
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Shoko Yoshida
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Linda Chang
- Neuroscience and Magnetic Resonance Research Program, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Susumu Mori
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
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Oishi K, Faria AV, Yoshida S, Chang L, Mori S. Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging. Int J Dev Neurosci 2013; 31:512-24. [PMID: 23796902 PMCID: PMC3830705 DOI: 10.1016/j.ijdevneu.2013.06.004] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2012] [Revised: 05/24/2013] [Accepted: 06/13/2013] [Indexed: 01/18/2023] Open
Abstract
The development of the brain is structure-specific, and the growth rate of each structure differs depending on the age of the subject. Magnetic resonance imaging (MRI) is often used to evaluate brain development because of the high spatial resolution and contrast that enable the observation of structure-specific developmental status. Currently, most clinical MRIs are evaluated qualitatively to assist in the clinical decision-making and diagnosis. The clinical MRI report usually does not provide quantitative values that can be used to monitor developmental status. Recently, the importance of image quantification to detect and evaluate mild-to-moderate anatomical abnormalities has been emphasized because these alterations are possibly related to several psychiatric disorders and learning disabilities. In the research arena, structural MRI and diffusion tensor imaging (DTI) have been widely applied to quantify brain development of the pediatric population. To interpret the values from these MR modalities, a "growth percentile chart," which describes the mean and standard deviation of the normal developmental curve for each anatomical structure, is required. Although efforts have been made to create such a growth percentile chart based on MRI and DTI, one of the greatest challenges is to standardize the anatomical boundaries of the measured anatomical structures. To avoid inter- and intra-reader variability about the anatomical boundary definition, and hence, to increase the precision of quantitative measurements, an automated structure parcellation method, customized for the neonatal and pediatric population, has been developed. This method enables quantification of multiple MR modalities using a common analytic framework. In this paper, the attempt to create an MRI- and a DTI-based growth percentile chart, followed by an application to investigate developmental abnormalities related to cerebral palsy, Williams syndrome, and Rett syndrome, have been introduced. Future directions include multimodal image analysis and personalization for clinical application.
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Affiliation(s)
- Kenichi Oishi
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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37
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Pagès G, Dvinskikh SV, Furó I. Suppressing magnetization exchange effects in stimulated-echo diffusion experiments. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2013; 234:35-43. [PMID: 23838524 DOI: 10.1016/j.jmr.2013.06.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2013] [Revised: 05/29/2013] [Accepted: 06/02/2013] [Indexed: 06/02/2023]
Abstract
Exchange of nuclear magnetization between spin pools, either by chemical exchange or by cross-relaxation or both, has a significant influence on the signal attenuation in stimulated-echo-type pulsed field gradient experiments. Hence, in such cases the obtained molecular self-diffusion coefficients can carry a large systematic error. We propose a modified stimulated echo pulse sequence that contains T2-filters during the z-magnetization store period. We demonstrate, using a common theoretical description for chemical exchange and cross-relaxation, that these filters suppress the effects of exchange on the diffusional decay in that frequent case where one of the participating spin pools is immobile and exhibits a short T2. We demonstrate the performance of this experiment in an agarose/water gel. We posit that this new experiment has advantages over other approaches hitherto used, such as that consisting of measuring separately the magnetization exchange rate, if suitable by Goldman-Shen type experiments, and then correcting for exchange effects within the framework of a two-site exchange model. We also propose experiments based on selective decoupling and applicable in systems with no large T2 difference between the different spin pools.
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Affiliation(s)
- Guilhem Pagès
- Division of Applied Physical Chemistry, Department of Chemistry, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden.
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38
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Bjarnason TA, Laule C, Bluman J, Kozlowski P. Temporal phase correction of multiple echo T2 magnetic resonance images. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2013; 231:22-31. [PMID: 23563572 PMCID: PMC5478376 DOI: 10.1016/j.jmr.2013.02.019] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2012] [Revised: 02/14/2013] [Accepted: 02/18/2013] [Indexed: 05/24/2023]
Abstract
Typically, magnetic resonance imaging (MRI) analysis is performed on magnitude data, and multiple echo T2 data consist of numerous images of the same slice taken with different echo spacing, giving voxel-wise temporal sampling of the noise as the signals decay according to T2 relaxation. Magnitude T2 decay data has Rician distributed noise which is characterized by a change in the noise distribution from Gaussian, through a transitional region, to Rayleigh as the signal to noise ratio decreases with increasing echo time. Non-Gaussian noise distributions may produce errors in the commonly applied non-negative least squares (NNLS) algorithm that is used to assess multiple echo decays for compartmentalized water environments through the creation of T2 distributions. Typically, Gaussian noise is sought by performing spatial-based phase correction on the MRI data however, these methods cannot capitalize on the temporal information available from multiple echo T2 acquisitions. Here we describe a temporal phase correction (TPC) algorithm that utilizes the temporal noise information available in multiple echo T2 acquisitions to put the relevant decay information in the Real portion of the decay data and leave only noise in the Imaginary portion. We apply this TPC algorithm to create real-valued multiple echo T2 data from human subjects measured at 1.5 T. We show that applying TPC causes changes in the T2 distribution estimates; notably the possible resolution of separate extracellular and intracellular water environments, and the disappearance of the commonly labeled cerebrospinal fluid peak, which might be an artefact observed in many previously published multiple echo T2 analyses.
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39
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What causes the hyperintense T2-weighting and increased short T2 signal in the corticospinal tract? Magn Reson Imaging 2013; 31:329-35. [DOI: 10.1016/j.mri.2012.07.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2012] [Revised: 06/30/2012] [Accepted: 07/08/2012] [Indexed: 11/23/2022]
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40
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The role of tissue microstructure and water exchange in biophysical modelling of diffusion in white matter. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2013; 26:345-70. [PMID: 23443883 PMCID: PMC3728433 DOI: 10.1007/s10334-013-0371-x] [Citation(s) in RCA: 100] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2012] [Revised: 01/28/2013] [Accepted: 02/01/2013] [Indexed: 12/27/2022]
Abstract
Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.
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41
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Nagy SA, Aradi M, Orsi G, Perlaki G, Kamson DO, Mike A, Komaromy H, Schwarcz A, Kovacs A, Janszky J, Pfund Z, Illes Z, Bogner P. Bi-exponential diffusion signal decay in normal appearing white matter of multiple sclerosis. Magn Reson Imaging 2013; 31:286-95. [DOI: 10.1016/j.mri.2012.07.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2012] [Revised: 07/03/2012] [Accepted: 07/15/2012] [Indexed: 10/28/2022]
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42
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Kara F, Chen F, Ronen I, de Groot HJM, Matysik J, Alia A. In vivo measurement of transverse relaxation time in the mouse brain at 17.6 T. Magn Reson Med 2012; 70:985-93. [PMID: 23161407 DOI: 10.1002/mrm.24533] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2012] [Revised: 09/26/2012] [Accepted: 09/27/2012] [Indexed: 11/09/2022]
Abstract
PURPOSE To establish regional T1 and T2 values of the healthy mouse brain at ultra-high magnetic field strength of 17.6 T and to follow regional brain T1 and T2 changes with age. METHODS In vivo T1 and T2 values in the C57BL/6J mouse brain were followed with age using multislice-multiecho sequence and multiple spin echo saturation recovery with variable repetition time sequence, respectively, at 9.4 and 17.6 T. Gadolinium-tetra-azacyclo-dodecane-tetra-acetic acid phantoms were used to validate in vivo T2 measurements. Student's t-test was used to compare mean relaxation values. RESULTS A field-dependent decrease in T2 is shown and validated with phantom measurements. T2 values at 17.6 T typically increased with age in multiple brain regions except in the hypothalamus and the caudate-putamen, where a slight decrease was observed. Furthermore, T1 values in various brain regions of young and old mice are presented at 17.6 T. A large gain in signal-to-noise ratio was observed at 17.6 T. CONCLUSIONS This study establishes for the first time the normative T1 and T2 values at 17.6 T over different mouse brain regions with age. The estimates of in vivo T1 and T2 will be useful to optimize pulse sequences for optimal image contrast at 17.6 T and will serve as baseline values against which disease-related relaxation changes can be assessed in mice.
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Affiliation(s)
- Firat Kara
- Solid State NMR, Leiden Institute of Chemistry, Gorlaeus Laboratoria, Leiden, The Netherlands
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43
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Luo J, Jagadeesan BD, Cross AH, Yablonskiy DA. Gradient echo plural contrast imaging--signal model and derived contrasts: T2*, T1, phase, SWI, T1f, FST2*and T2*-SWI. Neuroimage 2012; 60:1073-82. [PMID: 22305993 DOI: 10.1016/j.neuroimage.2012.01.108] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2011] [Revised: 01/11/2012] [Accepted: 01/20/2012] [Indexed: 10/14/2022] Open
Abstract
Gradient Echo Plural Contrast Imaging (GEPCI) is a post processing technique that, based on a widely available multiple gradient echo sequence, allows simultaneous generation of naturally co-registered images with various contrasts: T1 weighted, R2*=1/T2* maps and frequency (f) maps. Herein, we present results demonstrating the capability of GEPCI technique to generate image sets with additional contrast characteristics obtained by combing the information from these three basic contrast maps. Specifically, we report its ability to generate GEPCI-susceptibility weighted images (GEPCI-SWI) with improved SWI contrast that is free of T1 weighting and RF inhomogeneities; GEPCI-SWI-like images with the contrast similar to original SWI; T1f images that offer superior GM/WM matter contrast obtained by combining the GEPCI T1 and frequency map data; Fluid Suppressed T2* (FST2*) images that utilize GEPCI T1 data to suppress CSF signal in T2* maps and provide contrast similar to FLAIR T2 weighted images; and T2*-SWI images that combine SWI contrast with quantitative T2* map and offer advantages of visualizing venous structure with hyperintense T2* lesions (e.g. MS lesions). To analyze GEPCI images we use an improved algorithm for combining data from multi-channel RF coils and a method for unwrapping phase/frequency maps that takes advantage of the information on phase evolution as a function of gradient echo time in GEPCI echo train.
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Affiliation(s)
- Jie Luo
- Department of Chemistry, Washington University in St. Louis, One Brookings Drive, Saint Louis, MO 63130, USA
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44
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Diffusion MRI at 25: exploring brain tissue structure and function. Neuroimage 2011; 61:324-41. [PMID: 22120012 DOI: 10.1016/j.neuroimage.2011.11.006] [Citation(s) in RCA: 305] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2011] [Accepted: 11/02/2011] [Indexed: 12/14/2022] Open
Abstract
Diffusion MRI (or dMRI) came into existence in the mid-1980s. During the last 25 years, diffusion MRI has been extraordinarily successful (with more than 300,000 entries on Google Scholar for diffusion MRI). Its main clinical domain of application has been neurological disorders, especially for the management of patients with acute stroke. It is also rapidly becoming a standard for white matter disorders, as diffusion tensor imaging (DTI) can reveal abnormalities in white matter fiber structure and provide outstanding maps of brain connectivity. The ability to visualize anatomical connections between different parts of the brain, non-invasively and on an individual basis, has emerged as a major breakthrough for neurosciences. The driving force of dMRI is to monitor microscopic, natural displacements of water molecules that occur in brain tissues as part of the physical diffusion process. Water molecules are thus used as a probe that can reveal microscopic details about tissue architecture, either normal or in a diseased state.
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45
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In vivo assessment of myelination by phase imaging at high magnetic field. Neuroimage 2011; 59:1979-87. [PMID: 21985911 DOI: 10.1016/j.neuroimage.2011.09.057] [Citation(s) in RCA: 74] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2011] [Revised: 09/21/2011] [Accepted: 09/21/2011] [Indexed: 11/21/2022] Open
Abstract
The present study evaluated the potential of using the phase of T2* weighted MR images to characterize myelination during brain development and pathology in rodents at 9.4 T. Phase contrast correlated with myelin content assessed by histology and suggests that most contrast between white and cortical gray matter is modulated by myelin. Ex vivo experiments showed that gray-white matter phase contrast remains unchanged after iron extraction. In dysmyelinated shiverer mice, phase imaging correlated strongly with myelin staining, showing reduced contrast between white and gray matter when compared to healthy controls. We conclude that high-resolution phase images, acquired at high field, allow assessment of myelination and dysmyelination.
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46
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Ropele S, Langkammer C, Enzinger C, Fuchs S, Fazekas F. Relaxation time mapping in multiple sclerosis. Expert Rev Neurother 2011; 11:441-50. [PMID: 21375449 DOI: 10.1586/ern.10.129] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Several relaxation mapping techniques have been proposed to quantitatively assess disease-related brain tissue changes in multiple sclerosis. Newer developments also account for the distribution of hydrogen protons in different tissue compartments, and therefore provide markers for myelin and macromolecular content. This article will cover the broad spectrum of the pulse sequences and analysis techniques related to this topic that are currently available. Various technical and practical limitations linked with specific approaches will be discussed. These include acquisition time, accuracy and precision, radiofrequency absorption and limited coverage of the brain. Finally, the application of these techniques in the context of multiple sclerosis will be reviewed.
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47
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Hasan KM, Walimuni IS, Kramer LA, Narayana PA. Human brain iron mapping using atlas-based T2 relaxometry. Magn Reson Med 2011; 67:731-9. [PMID: 21702065 DOI: 10.1002/mrm.23054] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2011] [Revised: 05/23/2011] [Accepted: 05/24/2011] [Indexed: 01/09/2023]
Abstract
Several in vivo quantitative MRI techniques have been proposed as surrogate measures to map iron content in the human brain. The majority of in vivo quantitative MRI iron mapping methods used the age-dependent iron content data based on postmortem data. In this work, we fused atlas-based human brain volumetry obtained on a large cohort of healthy adults using FreeSurfer with T(2) relaxation time measurements. We provide a brain atlas-based T(2) relaxation time map, which was subsequently used along with published postmortem iron content data to obtain a map of iron content in subcortical and cortical gray matter. We have also investigated the sensitivity of the linear model relating transverse relaxation rate with published iron content to the number of regions used. Our work highlights the challenges encountered on using the simple model along with postmortem data to infer iron content in several brain regions where postmortem iron data are scant (e.g., corpus callosum, amygdale).
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Affiliation(s)
- Khader M Hasan
- Department of Diagnostic and Interventional Imaging, University of Texas Health Science Center at Houston, Houston, Texas 77030, USA.
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Kosior RK, Lauzon ML, Federico P, Frayne R. Algebraic T2 estimation improves detection of right temporal lobe epilepsy by MR T2 relaxometry. Neuroimage 2011; 58:189-97. [PMID: 21689766 DOI: 10.1016/j.neuroimage.2011.06.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2011] [Revised: 05/06/2011] [Accepted: 06/06/2011] [Indexed: 11/18/2022] Open
Abstract
Seizure related abnormalities may be detected with T2 relaxometry, which involves quantitative estimation of T2 values. Accounting for the partial-volume effect of cerebrospinal fluid (CSF) is important, especially for voxel-based relaxometry, VBR. With a mono-exponential decay model, this can be accomplished by including a baseline constant. An algebraic calculation, which accommodates this constant, offers improved T2 estimation speed over the commonly used non-linear fitting approach. Our objective was to compare the algebraic approach against three fitting approaches for the detection of seizure related abnormalities. We tested the performance of the four methods in the presence of noise using simulated data as well as real data acquired at 3 T with a Carr-Purcell-Meiboom-Gill sequence from 45 healthy subjects and 24 patients with confirmed right temporal lobe epilepsy. A quantitative analysis was performed on spatially normalized data by measuring T2 in various regions and with a whole brain tissue segmentation analysis. The detection rate of hippocampal T2 changes in patients was assessed by comparing the regional T2 measurements from each patient against the control data with a z-score threshold of 2.33. The algebraic method yielded high sensitivity for detection of hippocampal abnormalities in the epileptic patients in regional assessment and in follow-up single-subject VBR. This can be attributed to the relatively small variance across healthy subjects and improved precision in the presence of CSF and noise in simulation. In conclusion, the algebraic method is better than fitting based on faster calculation speed and better sensitivity for detecting seizure-related T2 changes.
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Affiliation(s)
- Robert K Kosior
- Department of Biomedical Engineering, University of Calgary, Calgary, Alberta, Canada
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Walimuni IS, Hasan KM. Atlas-based investigation of human brain tissue microstructural spatial heterogeneity and interplay between transverse relaxation time and radial diffusivity. Neuroimage 2011; 57:1402-10. [PMID: 21658457 DOI: 10.1016/j.neuroimage.2011.05.063] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2011] [Revised: 05/16/2011] [Accepted: 05/21/2011] [Indexed: 01/05/2023] Open
Abstract
Microstructural metrics obtained using magnetic resonance imaging (MRI) such as transverse relaxation time and radial diffusivity have been used as in vivo markers of human brain tissue integrity. Considering the sensitivity of these parameters to some common biophysical contributors and their structural and spatial heterogeneity, we hypothesized that strong inter and intra-regional associations exist between these variables providing evidence to possible interplay between transverse relaxation time and radial diffusivity. To validate our hypothesis we obtained high resolution anatomical T1-weighted data and fused it with T2-relaxometry and diffusion tensor imaging (DTI) data on a cohort of healthy adults. The anatomical data were parcellated using FreeSurfer and then coaligned and fused with the T2 and DTI maps. Our data reveal some association between transverse relaxation and radial diffusivity that may help toward the interpretation and modeling of the biophysical contributors to the measured MRI metrics.
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Affiliation(s)
- Indika S Walimuni
- Department of Diagnostic and Interventional Imaging, University of Texas Health Science Center at Houston-Medical School, Houston, Texas 77030, USA
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50
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Shah NJ, Ermer V, Oros-Peusquens AM. Measuring the absolute water content of the brain using quantitative MRI. Methods Mol Biol 2011; 711:29-64. [PMID: 21279597 DOI: 10.1007/978-1-61737-992-5_3] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Methods for quantitative imaging of the brain are presented and compared. Highly precise and accurate mapping of the absolute water content and distribution, as presented here, requires a significant number of corrections and also involves mapping of other MR parameters. Here, either T(1) and T(2)(*) or T(2) is mapped, and several corrections involving the measurement of temperature, transmit and receive B(1) inhomogeneities and signal extrapolation to zero TE are applied. Information about the water content of the whole brain can be acquired in clinically acceptable measurement times (10 or 20 min). Since water content is highly regulated in the healthy brain, pathological changes can be easily identified and their evolution or correlation with other manifestations of the disease investigated. In addition to voxel-based total water content, information about the different environments of water can be gleaned from qMRI. The myelin water fraction can be extracted from the fit of very high-SNR multiple-echo T(2) decay curves with a superposition of a large number of exponentials. Diseases involving de- or dysmyelination can be investigated and lead to novel observations regarding the water compartmentalisation in tissue, despite the limited spatial coverage. In conclusion, quantitative MRI is emerging as an unparalleled tool for the study of the normal and diseased brain, replacing the customary time-space environment of the sequential mixed-contrast MRI with a multi-NMR-parametric space in which tissue microscopy is increasingly revealed.
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Affiliation(s)
- Nadim Joni Shah
- Institute of Neuroscience and Medicine (INM-4), Research Centre Juelich, Juelich, Germany.
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