1
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Ulloa P, Methot V, Wottschel V, Koch MA. Extra-axonal contribution to double diffusion encoding-based pore size estimates in the corticospinal tract. MAGMA (NEW YORK, N.Y.) 2023; 36:589-612. [PMID: 36745290 PMCID: PMC10468962 DOI: 10.1007/s10334-022-01058-8] [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: 05/25/2022] [Revised: 12/14/2022] [Accepted: 12/19/2022] [Indexed: 02/07/2023]
Abstract
OBJECTIVE To study the origin of compartment size overestimation in double diffusion encoding MRI (DDE) in vivo experiments in the human corticospinal tract. Here, the extracellular space is hypothesized to be the origin of the DDE signal. By exploiting the DDE sensitivity to pore shape, it could be possible to identify the origin of the measured signal. The signal difference between parallel and perpendicular diffusion gradient orientation can indicate if a compartment is regular or eccentric in shape. As extracellular space can be considered an eccentric compartment, a positive difference would mean a high contribution to the compartment size estimates. MATERIALS AND METHODS Computer simulations using MISST and in vivo experiments in eight healthy volunteers were performed. DDE experiments using a double spin-echo preparation with eight perpendicular directions were measured in vivo. The difference between parallel and perpendicular gradient orientations was analyzed using a Wilcoxon signed-rank test and a Mann-Whitney U test. RESULTS Simulations and MR experiments showed a statistically significant difference between parallel and perpendicular diffusion gradient orientation signals ([Formula: see text]). CONCLUSION The results suggest that the DDE-based size estimate may be considerably influenced by the extra-axonal compartment. However, the experimental results are also consistent with purely intra-axonal contributions in combination with a large fiber orientation dispersion.
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Affiliation(s)
- Patricia Ulloa
- Institute of Medical Engineering, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany
| | - Vincent Methot
- Institute of Medical Engineering, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany
| | - Viktor Wottschel
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, De Boelelaan 1117, 1081, Amsterdam, The Netherlands
| | - Martin A. Koch
- Institute of Medical Engineering, University of Luebeck, Ratzeburger Allee 160, 23562 Luebeck, Germany
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2
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Hennel F, Dillinger H, Leupold J, Pruessmann KP. Fourier transform temporal diffusion spectroscopy. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2023; 348:107401. [PMID: 36774713 DOI: 10.1016/j.jmr.2023.107401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 01/04/2023] [Accepted: 02/03/2023] [Indexed: 06/18/2023]
Abstract
Temporal diffusion spectroscopy (TDS) currently uses the oscillating gradient spin echo (OGSE) experiment to measure the spectral density of translational velocity autocorrelation at single frequencies. Due to timing restrictions imposed by the transverse relaxation, the frequency selectivity and the sampling density of OGSE are limited, especially at low frequencies. We propose to overcome this problem by adopting the principles of Fourier transform spectroscopy. The new method of Fourier transform TDS (FTDS) uses two broadband gradient waveforms with different relative delays to make the spin echo attenuation sensitive to a broad range of diffusion frequencies with different harmonic modulations and calculates the spectrum by discrete Fourier transform. The method was validated by a measurement of diffusion spectra in highly restrictive tissues of a celery stalk and provided results consistent with OGSE, however, on a denser frequency grid.
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Affiliation(s)
- Franciszek Hennel
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.
| | - Hannes Dillinger
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Jochen Leupold
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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3
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Afzali M, Pieciak T, Newman S, Garyfallidis E, Özarslan E, Cheng H, Jones DK. The sensitivity of diffusion MRI to microstructural properties and experimental factors. J Neurosci Methods 2021; 347:108951. [PMID: 33017644 PMCID: PMC7762827 DOI: 10.1016/j.jneumeth.2020.108951] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 08/27/2020] [Accepted: 09/15/2020] [Indexed: 12/13/2022]
Abstract
Diffusion MRI is a non-invasive technique to study brain microstructure. Differences in the microstructural properties of tissue, including size and anisotropy, can be represented in the signal if the appropriate method of acquisition is used. However, to depict the underlying properties, special care must be taken when designing the acquisition protocol as any changes in the procedure might impact on quantitative measurements. This work reviews state-of-the-art methods for studying brain microstructure using diffusion MRI and their sensitivity to microstructural differences and various experimental factors. Microstructural properties of the tissue at a micrometer scale can be linked to the diffusion signal at a millimeter-scale using modeling. In this paper, we first give an introduction to diffusion MRI and different encoding schemes. Then, signal representation-based methods and multi-compartment models are explained briefly. The sensitivity of the diffusion MRI signal to the microstructural components and the effects of curvedness of axonal trajectories on the diffusion signal are reviewed. Factors that impact on the quality (accuracy and precision) of derived metrics are then reviewed, including the impact of random noise, and variations in the acquisition parameters (i.e., number of sampled signals, b-value and number of acquisition shells). Finally, yet importantly, typical approaches to deal with experimental factors are depicted, including unbiased measures and harmonization. We conclude the review with some future directions and recommendations on this topic.
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Affiliation(s)
- Maryam Afzali
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.
| | - Tomasz Pieciak
- AGH University of Science and Technology, Kraków, Poland; LPI, ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain.
| | - Sharlene Newman
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Program of Neuroscience, Indiana University, Bloomington, IN 47405, USA.
| | - Eleftherios Garyfallidis
- Program of Neuroscience, Indiana University, Bloomington, IN 47405, USA; Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN 47408, USA.
| | - Evren Özarslan
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
| | - Hu Cheng
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Program of Neuroscience, Indiana University, Bloomington, IN 47405, USA.
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.
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4
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Henriques RN, Palombo M, Jespersen SN, Shemesh N, Lundell H, Ianuş A. Double diffusion encoding and applications for biomedical imaging. J Neurosci Methods 2020; 348:108989. [PMID: 33144100 DOI: 10.1016/j.jneumeth.2020.108989] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 09/25/2020] [Accepted: 10/20/2020] [Indexed: 12/11/2022]
Abstract
Diffusion Magnetic Resonance Imaging (dMRI) is one of the most important contemporary non-invasive modalities for probing tissue structure at the microscopic scale. The majority of dMRI techniques employ standard single diffusion encoding (SDE) measurements, covering different sequence parameter ranges depending on the complexity of the method. Although many signal representations and biophysical models have been proposed for SDE data, they are intrinsically limited by a lack of specificity. Advanced dMRI methods have been proposed to provide additional microstructural information beyond what can be inferred from SDE. These enhanced contrasts can play important roles in characterizing biological tissues, for instance upon diseases (e.g. neurodegenerative, cancer, stroke), aging, learning, and development. In this review we focus on double diffusion encoding (DDE), which stands out among other advanced acquisitions for its versatility, ability to probe more specific diffusion correlations, and feasibility for preclinical and clinical applications. Various DDE methodologies have been employed to probe compartment sizes (Section 3), decouple the effects of microscopic diffusion anisotropy from orientation dispersion (Section 4), probe displacement correlations, study exchange, or suppress fast diffusing compartments (Section 6). DDE measurements can also be used to improve the robustness of biophysical models (Section 5) and study intra-cellular diffusion via magnetic resonance spectroscopy of metabolites (Section 7). This review discusses all these topics as well as important practical aspects related to the implementation and contrast in preclinical and clinical settings (Section 9) and aims to provide the readers a guide for deciding on the right DDE acquisition for their specific application.
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Affiliation(s)
- Rafael N Henriques
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Marco Palombo
- Centre for Medical Image Computing and Dept. of Computer Science, University College London, London, UK
| | - Sune N Jespersen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
| | - Noam Shemesh
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Henrik Lundell
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark
| | - Andrada Ianuş
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal.
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5
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Novikov DS, Fieremans E, Jespersen SN, Kiselev VG. Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation. NMR IN BIOMEDICINE 2019; 32:e3998. [PMID: 30321478 PMCID: PMC6481929 DOI: 10.1002/nbm.3998] [Citation(s) in RCA: 248] [Impact Index Per Article: 49.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Revised: 06/11/2018] [Accepted: 06/28/2018] [Indexed: 05/18/2023]
Abstract
We review, systematize and discuss models of diffusion in neuronal tissue, by putting them into an overarching physical context of coarse-graining over an increasing diffusion length scale. From this perspective, we view research on quantifying brain microstructure as occurring along three major avenues. The first avenue focusses on transient, or time-dependent, effects in diffusion. These effects signify the gradual coarse-graining of tissue structure, which occurs qualitatively differently in different brain tissue compartments. We show that transient effects contain information about the relevant length scales for neuronal tissue, such as the packing correlation length for neuronal fibers, as well as the degree of structural disorder along the neurites. The second avenue corresponds to the long-time limit, when the observed signal can be approximated as a sum of multiple nonexchanging anisotropic Gaussian components. Here, the challenge lies in parameter estimation and in resolving its hidden degeneracies. The third avenue employs multiple diffusion encoding techniques, able to access information not contained in the conventional diffusion propagator. We conclude with our outlook on future directions that could open exciting possibilities for designing quantitative markers of tissue physiology and pathology, based on methods of studying mesoscopic transport in disordered systems.
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Affiliation(s)
- Dmitry S. Novikov
- Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY, USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, NY, USA
| | - Sune N. Jespersen
- CFIN/MINDLab, Department of Clinical Medicine and Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
| | - Valerij G. Kiselev
- Medical Physics, Deptartment of Radiology, Faculty of Medicine, University of Freiburg, Germany
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6
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Ji Y, Lu D, Wu L, Qiu B, Song YQ, Sun PZ. Preliminary evaluation of accelerated microscopic diffusional kurtosis imaging (μDKI) in a rodent model of epilepsy. Magn Reson Imaging 2018; 56:90-95. [PMID: 30352270 DOI: 10.1016/j.mri.2018.10.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 10/15/2018] [Accepted: 10/18/2018] [Indexed: 12/23/2022]
Abstract
PURPOSE Our study aimed to develop accelerated microscopic diffusional kurtosis imaging (μDKI) and preliminarily evaluated it in a rodent model of chronic epilepsy. METHODS We investigated two μDKI acceleration schemes of reduced sampling density and angular range in a phantom and wild-type rats, and further tested μDKI method in pilocarpine-induced epilepsy rats using a 4.7 Tesla MRI. Single slice average μDapp and μKapp maps were derived, and Nissl staining was obtained. RESULTS The kurtosis maps from two accelerated μDKI sampling schemes (sampling density and range) are very similar to that using fully sampled data (SSIM > 0.95). For the epileptic models, μDKI showed noticeably different contrast from those obtained with conventional DKI. Specifically, the average μKapp was significantly less than that of the average of Kapp (0.15 ± 0.01 vs. 0.47 ± 0.02) in the ventricle. CONCLUSIONS Our study demonstrated the feasibility of accelerated in vivo μDKI. Our work revealed that μDKI provides complementary information to conventional DKI method, suggesting that advanced DKI sequences are promising to elucidate tissue microstructure in neurological diseases.
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Affiliation(s)
- Yang Ji
- Center for Biomedical Engineering, Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, China; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States of America
| | - Dongshuang Lu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States of America
| | - Limin Wu
- Neuroscience Center, Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States of America
| | - Bensheng Qiu
- Center for Biomedical Engineering, Department of Electronic Science and Technology, University of Science and Technology of China, Hefei, China
| | - Yi-Qiao Song
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States of America; Schlumberger-Doll Research Center, Cambridge, MA, United States of America
| | - Phillip Zhe Sun
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States of America; Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States of America; Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States of America.
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7
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Zong F, Ancelet LR, Hermans IF, Galvosas P. Determining mean fractional anisotropy using DDCOSY: preliminary results in biological tissues. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2017; 55:498-507. [PMID: 27487091 DOI: 10.1002/mrc.4492] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Revised: 07/19/2016] [Accepted: 07/22/2016] [Indexed: 06/06/2023]
Abstract
Complex materials are ubiquitous in science, engineering and nature. One important parameter for characterising their morphology is the degree of anisotropy. Magnetic resonance imaging offers non-invasive methods for quantitative measurements of the materials anisotropy, most commonly via diffusion tensor imaging and the subsequent extraction of the spatially resolved fractional anisotropy (FA) value. Here, we propose an alternative way of determining the FA as a sample average for cases where spatially resolved methods are not needed or not applicable. It is based on a particular diffusion-diffusion correlation spectroscopy protocol, allowing for the extraction of the mean (i.e. sample averaged) FA value. We demonstrate that mean FA values obtained from three anisotropic biological tissues are consistent with those extracted using diffusion tensor imaging. Moreover, we show that differences of mean FA values in healthy and tumour-bearing mouse brains allow to distinguish these tissue types. We anticipate that the proposed method will be beneficial in the wider context of medical and material science. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Fangrong Zong
- MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Chemical and Physical Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Lindsay R Ancelet
- Malaghan Institute of Medical Research, Wellington, New Zealand
- Maurice Wilkins Centre, Auckland, New Zealand
| | - Ian F Hermans
- Malaghan Institute of Medical Research, Wellington, New Zealand
- Maurice Wilkins Centre, Auckland, New Zealand
- School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
| | - Petrik Galvosas
- MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Chemical and Physical Sciences, Victoria University of Wellington, Wellington, New Zealand
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8
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Morozov D, Tal I, Pisanty O, Shani E, Cohen Y. Studying microstructure and microstructural changes in plant tissues by advanced diffusion magnetic resonance imaging techniques. JOURNAL OF EXPERIMENTAL BOTANY 2017; 68:2245-2257. [PMID: 28398563 PMCID: PMC5447889 DOI: 10.1093/jxb/erx106] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
As sessile organisms, plants must respond to the environment by adjusting their growth and development. Most of the plant body is formed post-embryonically by continuous activity of apical and lateral meristems. The development of lateral adventitious roots is a complex process, and therefore the development of methods that can visualize, non-invasively, the plant microstructure and organ initiation that occur during growth and development is of paramount importance. In this study, relaxation-based and advanced diffusion magnetic resonance imaging (MRI) methods including diffusion tensor (DTI), q-space diffusion imaging (QSI), and double-pulsed-field-gradient (d-PFG) MRI, at 14.1 T, were used to characterize the hypocotyl microstructure and the microstructural changes that occurred during the development of lateral adventitious roots in tomato. Better contrast was observed in relaxation-based MRI using higher in-plane resolution but this also resulted in a significant reduction in the signal-to-noise ratio of the T2-weighted MR images. Diffusion MRI revealed that water diffusion is highly anisotropic in the vascular cylinder. QSI and d-PGSE MRI showed that in the vascular cylinder some of the cells have sizes in the range of 6-10 μm. The MR images captured cell reorganization during adventitious root formation in the periphery of the primary vascular bundles, adjacent to the xylem pole that broke through the cortex and epidermis layers. This study demonstrates that MRI and diffusion MRI methods allow the non-invasive study of microstructural features of plants, and enable microstructural changes associated with adventitious root formation to be followed.
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Affiliation(s)
- Darya Morozov
- School of Chemistry, The Sackler Faculty of Exact Sciences, and
| | - Iris Tal
- Department of Molecular Biology and Ecology of Plants, Tel Aviv University, Ramat Aviv, Tel Aviv 66978, Israel
| | - Odelia Pisanty
- Department of Molecular Biology and Ecology of Plants, Tel Aviv University, Ramat Aviv, Tel Aviv 66978, Israel
| | - Eilon Shani
- Department of Molecular Biology and Ecology of Plants, Tel Aviv University, Ramat Aviv, Tel Aviv 66978, Israel
| | - Yoram Cohen
- School of Chemistry, The Sackler Faculty of Exact Sciences, and
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9
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Shemesh N, Jespersen SN, Alexander DC, Cohen Y, Drobnjak I, Dyrby TB, Finsterbusch J, Koch MA, Kuder T, Laun F, Lawrenz M, Lundell H, Mitra PP, Nilsson M, Özarslan E, Topgaard D, Westin CF. Conventions and nomenclature for double diffusion encoding NMR and MRI. Magn Reson Med 2015; 75:82-7. [DOI: 10.1002/mrm.25901] [Citation(s) in RCA: 140] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2015] [Revised: 07/13/2015] [Accepted: 07/29/2015] [Indexed: 11/06/2022]
Affiliation(s)
- Noam Shemesh
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown; Lisbon Portugal
| | - Sune N. Jespersen
- CFIN/MindLab, Aarhus University; Aarhus Denmark
- Department of Physics and Astronomy; Aarhus University; Aarhus Denmark
| | - Daniel C. Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London; London United Kingdom
| | - Yoram Cohen
- School of Chemistry, the Raymond and Beverly Sackler Faculty of Exact Sciences; Tel Aviv University; Tel Aviv Israel
- Sagol School of Neurosciences; Tel Aviv University; Tel Aviv Israel
| | - Ivana Drobnjak
- Centre for Medical Image Computing, Department of Computer Science, University College London; London United Kingdom
| | - Tim B. Dyrby
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre; Hvidovre Denmark
| | - Jurgen Finsterbusch
- Department of Systems Neuroscience; University Medical Center Hamburg-Eppendorf; Hamburg Germany
- Neuroimage Nord, University Medical Centers Hamburg-Kiel-Lübeck; Germany
| | - Martin A. Koch
- Institute of Medical Engineering; University of Lübeck; Lübeck Germany
| | - Tristan Kuder
- Medical Physics in Radiology, German Cancer Research Center; Im Neuenheimer Feld 280 Heidelberg Germany
| | - Fredrik Laun
- Medical Physics in Radiology, German Cancer Research Center; Im Neuenheimer Feld 280 Heidelberg Germany
| | - Marco Lawrenz
- Department of Systems Neuroscience; University Medical Center Hamburg-Eppendorf; Hamburg Germany
| | - Henrik Lundell
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre; Hvidovre Denmark
| | - Partha P. Mitra
- Cold Spring Harbor Laboratory; Cold Spring Harbor New York USA
| | - Markus Nilsson
- Lund University Bioimaging Center, Lund University; Lund Sweden
| | - Evren Özarslan
- Department of Physics; Boğaziçi University; Bebek Istanbul Turkey
| | - Daniel Topgaard
- Division of Physical Chemistry, Department of Chemistry; Lund University; Lund Sweden
| | - Carl-Fredrik Westin
- Department of Radiology, Brigham and Women's Hospital; Harvard Medical School; Boston Massachusetts USA
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10
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Özarslan E, Westin CF, Mareci TH. Characterizing magnetic resonance signal decay due to Gaussian diffusion: the path integral approach and a convenient computational method. CONCEPTS IN MAGNETIC RESONANCE. PART A, BRIDGING EDUCATION AND RESEARCH 2015; 44:203-213. [PMID: 27182208 PMCID: PMC4864615 DOI: 10.1002/cmr.a.21354] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
The influence of Gaussian diffusion on the magnetic resonance signal is determined by the apparent diffusion coefficient (ADC) and tensor (ADT) of the diffusing fluid as well as the gradient waveform applied to sensitize the signal to diffusion. Estimations of ADC and ADT from diffusion-weighted acquisitions necessitate computations of, respectively, the b-value and b-matrix associated with the employed pulse sequence. We establish the relationship between these quantities and the gradient waveform by expressing the problem as a path integral and explicitly evaluating it. Further, we show that these important quantities can be conveniently computed for any gradient waveform using a simple algorithm that requires a few lines of code. With this representation, our technique complements the multiple correlation function (MCF) method commonly used to compute the effects of restricted diffusion, and provides a consistent and convenient framework for studies that aim to infer the microstructural features of the specimen.
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Affiliation(s)
- Evren Özarslan
- Department of Physics, Bođaziçi University, Bebek, Ýstanbul, Turkey
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Corresponding author.
| | - Carl-Fredrik Westin
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Thomas H. Mareci
- Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, USA
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11
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Morozov D, Bar L, Sochen N, Cohen Y. Microstructural information from angular double-pulsed-field-gradient NMR: From model systems to nerves. Magn Reson Med 2014; 74:25-32. [DOI: 10.1002/mrm.25371] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2013] [Revised: 06/24/2014] [Accepted: 06/24/2014] [Indexed: 11/11/2022]
Affiliation(s)
- Darya Morozov
- School of Chemistry, The Raymond and Beverly Sackler Faculty of Exact Science, Tel Aviv University; Tel Aviv Israel
| | - Leah Bar
- School of Mathematical Sciences, The Raymond and Beverly Sackler Faculty of Exact Science, Tel Aviv University; Tel Aviv Israel
| | - Nir Sochen
- School of Mathematical Sciences, The Raymond and Beverly Sackler Faculty of Exact Science, Tel Aviv University; Tel Aviv Israel
| | - Yoram Cohen
- School of Chemistry, The Raymond and Beverly Sackler Faculty of Exact Science, Tel Aviv University; Tel Aviv Israel
- Sagol School of Neuroscience, Tel Aviv University; Tel Aviv Israel
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12
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Komlosh ME, Özarslan E, Lizak MJ, Horkayne-Szakaly I, Freidlin RZ, Horkay F, Basser PJ. Mapping average axon diameters in porcine spinal cord white matter and rat corpus callosum using d-PFG MRI. Neuroimage 2013; 78:210-6. [PMID: 23583426 DOI: 10.1016/j.neuroimage.2013.03.074] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2012] [Revised: 03/11/2013] [Accepted: 03/28/2013] [Indexed: 11/15/2022] Open
Abstract
Knowledge of microstructural features of nerve fascicles, such as their axon diameter, is crucial for understanding normal function in the central and peripheral nervous systems as well as assessing changes due to pathologies. In this study double-pulsed field gradient (d-PFG) filtered MRI was used to map the average axon diameter (AAD) in porcine spinal cord, which was then compared to AADs measured with optical microscopy of the same specimen, as a way to further validate this new MRI method. A novel 3D d-PFG acquisition scheme was used to obtain AADs in each voxel of a coronal slice of rat brain corpus callosum. AAD measurements were also acquired using optical microscopy performed on histological sections and validated using a glass capillary array phantom.
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Affiliation(s)
- M E Komlosh
- Section on Tissue Biophysics and Biomimetics, PPITS, NICHD, National Institutes of Health, Bethesda, MD 20892, USA.
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13
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Morozov D, Bar L, Sochen N, Cohen Y. Measuring small compartments with relatively weak gradients by angular double-pulsed-field-gradient NMR. Magn Reson Imaging 2013; 31:401-7. [DOI: 10.1016/j.mri.2012.08.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2012] [Accepted: 08/31/2012] [Indexed: 11/30/2022]
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14
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Avram AV, Özarslan E, Sarlls JE, Basser PJ. In vivo detection of microscopic anisotropy using quadruple pulsed-field gradient (qPFG) diffusion MRI on a clinical scanner. Neuroimage 2013; 64:229-39. [PMID: 22939872 PMCID: PMC3520437 DOI: 10.1016/j.neuroimage.2012.08.048] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2012] [Revised: 08/02/2012] [Accepted: 08/18/2012] [Indexed: 11/20/2022] Open
Abstract
We report our design and implementation of a quadruple pulsed-field gradient (qPFG) diffusion MRI pulse sequence on a whole-body clinical scanner and demonstrate its ability to non-invasively detect restriction-induced microscopic anisotropy in human brain tissue. The microstructural information measured using qPFG diffusion MRI in white matter complements that provided by diffusion tensor imaging (DTI) and exclusively characterizes diffusion of water trapped in microscopic compartments with unique measures of average cell geometry. We describe the effect of white matter fiber orientation on the expected MR signal and highlight the importance of incorporating such information in the axon diameter measurement using a suitable mathematical framework. Integration of qPFG diffusion-weighted images (DWI) with fiber orientations measured using high-resolution DTI allows the estimation of average axon diameters in the corpus callosum of healthy human volunteers. Maps of inter-hemispheric average axon diameters reveal an anterior-posterior variation in good topographical agreement with anatomical measurements reported in previous post-mortem studies. With further technical refinements and additional clinical validation, qPFG diffusion MRI could provide a quantitative whole-brain histological assessment of white and gray matter, enabling a wide range of neuroimaging applications for improved diagnosis of neurodegenerative pathologies, monitoring neurodevelopmental processes, and mapping brain connectivity.
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Affiliation(s)
- Alexandru V Avram
- Section on Tissue Biophysics and Biomimetics, PPITS, NICHD, National Institutes of Health, Bethesda, MD 20892, USA.
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Lawrenz M, Finsterbusch J. Double-wave-vector diffusion-weighted imaging reveals microscopic diffusion anisotropy in the living human brain. Magn Reson Med 2012; 69:1072-82. [DOI: 10.1002/mrm.24347] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2012] [Revised: 04/27/2012] [Accepted: 04/30/2012] [Indexed: 11/05/2022]
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