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Bosticardo S, Schiavi S, Schaedelin S, Battocchio M, Barakovic M, Lu PJ, Weigel M, Melie-Garcia L, Granziera C, Daducci A. Evaluation of tractography-based myelin-weighted connectivity across the lifespan. Front Neurosci 2024; 17:1228952. [PMID: 38239829 PMCID: PMC10794573 DOI: 10.3389/fnins.2023.1228952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 12/04/2023] [Indexed: 01/22/2024] Open
Abstract
Introduction Recent studies showed that the myelin of the brain changes in the life span, and demyelination contributes to the loss of brain plasticity during normal aging. Diffusion-weighted magnetic resonance imaging (dMRI) allows studying brain connectivity in vivo by mapping axons in white matter with tractography algorithms. However, dMRI does not provide insight into myelin; thus, combining tractography with myelin-sensitive maps is necessary to investigate myelin-weighted brain connectivity. Tractometry is designated for this purpose, but it suffers from some serious limitations. Our study assessed the effectiveness of the recently proposed Myelin Streamlines Decomposition (MySD) method in estimating myelin-weighted connectomes and its capacity to detect changes in myelin network architecture during the process of normal aging. This approach opens up new possibilities compared to traditional Tractometry. Methods In a group of 85 healthy controls aged between 18 and 68 years, we estimated myelin-weighted connectomes using Tractometry and MySD, and compared their modulation with age by means of three well-known global network metrics. Results Following the literature, our results show that myelin development continues until brain maturation (40 years old), after which degeneration begins. In particular, mean connectivity strength and efficiency show an increasing trend up to 40 years, after which the process reverses. Both Tractometry and MySD are sensitive to these changes, but MySD turned out to be more accurate. Conclusion After regressing the known predictors, MySD results in lower residual error, indicating that MySD provides more accurate estimates of myelin-weighted connectivity than Tractometry.
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Affiliation(s)
- Sara Bosticardo
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Simona Schiavi
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
- ASG Superconductors S.p.A., Genoa, Italy
| | - Sabine Schaedelin
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Matteo Battocchio
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d’Informatique, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Lester Melie-Garcia
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Alessandro Daducci
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
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Chau Loo Kung G, Knowles JK, Batra A, Ni L, Rosenberg J, McNab JA. Quantitative MRI reveals widespread, network-specific myelination change during generalized epilepsy progression. Neuroimage 2023; 280:120312. [PMID: 37574120 PMCID: PMC11095339 DOI: 10.1016/j.neuroimage.2023.120312] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 06/17/2023] [Accepted: 08/04/2023] [Indexed: 08/15/2023] Open
Abstract
Activity-dependent myelination is a fundamental mode of brain plasticity which significantly influences network function. We recently discovered that absence seizures, which occur in multiple forms of generalized epilepsy, can induce activity-dependent myelination, which in turn promotes further progression of epilepsy. Structural alterations of myelin are likely to be widespread, given that absence seizures arise from an extensive thalamocortical network involving frontoparietal regions of the bilateral hemispheres. However, the temporal course and spatial extent of myelin plasticity is unknown, due to limitations of gold-standard histological methods such as electron microscopy (EM). In this study, we leveraged magnetization transfer and diffusion MRI for estimation of g-ratios across major white matter tracts in a mouse model of generalized epilepsy with progressive absence seizures. EM was performed on the same brains after MRI. After seizure progression, we found increased myelination (decreased g-ratios) throughout the anterior portion (genu-to-body) of the corpus callosum but not in the posterior portion (body-splenium) nor in the fornix or the internal capsule. Curves obtained from averaging g-ratio values at every longitudinal point of the corpus callosum were statistically different with p<0.001. Seizure-associated myelin differences found in the corpus callosum body with MRI were statistically significant (p = 0.0027) and were concordant with EM in the same region (p = 0.01). Notably, these differences were not detected by diffusion tensor imaging. This study reveals widespread myelin structural change that is specific to the absence seizure network. Furthermore, our findings demonstrate the potential utility and importance of MRI-based g-ratio estimation to non-invasively detect myelin plasticity.
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Affiliation(s)
- Gustavo Chau Loo Kung
- Bioengineering Department, Stanford University, 443 Via Ortega, Stanford, CA 94305, United States; Radiology Department, Stanford University, 1201 Welch Rd, Stanford, CA 94305, United States.
| | - Juliet K Knowles
- Neurology Department, 1701 Page Mill Road, Palo Alto, CA 94304, United States.
| | - Ankita Batra
- Neurology Department, 1701 Page Mill Road, Palo Alto, CA 94304, United States.
| | - Lijun Ni
- Neurology Department, SIM1 G3035, Stanford, CA 94305, United States.
| | - Jarrett Rosenberg
- Radiology Department, Stanford University, 1201 Welch Rd, Stanford, CA 94305, United States.
| | - Jennifer A McNab
- Radiology Department, Stanford University, 1201 Welch Rd, Stanford, CA 94305, United States.
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3
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Wang Z, Zhang L, Yang Y, Wang Q, Qu S, Wang X, He Z, Luan Z. Oligodendrocyte Progenitor Cell Transplantation Ameliorates Preterm Infant Cerebral White Matter Injury in Rats Model. Neuropsychiatr Dis Treat 2023; 19:1935-1947. [PMID: 37719062 PMCID: PMC10503552 DOI: 10.2147/ndt.s414493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 08/24/2023] [Indexed: 09/19/2023] Open
Abstract
Background Cerebral white matter injury (WMI) is the most common brain injury in preterm infants, leading to motor and developmental deficits often accompanied by cognitive impairment. However, there is no effective treatment. One promising approach for treating preterm WMI is cell replacement therapy, in which lost cells can be replaced by exogenous oligodendrocyte progenitor cells (OPCs). Methods This study developed a method to differentiate human neural stem cells (hNSCs) into human OPCs (hOPCs). The preterm WMI animal model was established in rats on postnatal day 3, and OLIG2+/NG2+/PDGFRα+/O4+ hOPCs were enriched and transplanted into the corpus callosum on postnatal day 10. Then, histological analysis and electron microscopy were used to detect lesion structure; behavioral assays were performed to detect cognitive function. Results Transplanted hOPCs survived and migrated throughout the major white matter tracts. Morphological differentiation of transplanted hOPCs was observed. Histological analysis revealed structural repair of lesioned areas. Re-myelination of the axons in the corpus callosum was confirmed by electron microscopy. The Morris water maze test revealed cognitive function recovery. Conclusion Our study showed that exogenous hOPCs could differentiate into CC1+ OLS in the brain of WMI rats, improving their cognitive functions.
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Affiliation(s)
- Zhaoyan Wang
- Laboratory of Pediatrics, The Sixth Medical Center of PLA General Hospital, Beijing, 100048, People’s Republic of China
| | - Leping Zhang
- Laboratory of Pediatrics, The Sixth Medical Center of PLA General Hospital, Beijing, 100048, People’s Republic of China
- Guizhou Medical University, Guiyang, 550004, People’s Republic of China
| | - Yinxiang Yang
- Laboratory of Pediatrics, The Sixth Medical Center of PLA General Hospital, Beijing, 100048, People’s Republic of China
| | - Qian Wang
- Laboratory of Pediatrics, The Sixth Medical Center of PLA General Hospital, Beijing, 100048, People’s Republic of China
| | - Suqing Qu
- Laboratory of Pediatrics, The Sixth Medical Center of PLA General Hospital, Beijing, 100048, People’s Republic of China
| | - Xiaohua Wang
- Laboratory of Pediatrics, The Sixth Medical Center of PLA General Hospital, Beijing, 100048, People’s Republic of China
| | - Zhixu He
- Guizhou Medical University, Guiyang, 550004, People’s Republic of China
- Department of Pediatrics, Affiliated Hospital of Zunyi Medical University, Zunyi, 563100, People’s Republic of China
| | - Zuo Luan
- Laboratory of Pediatrics, The Sixth Medical Center of PLA General Hospital, Beijing, 100048, People’s Republic of China
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4
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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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5
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Shepilov D, Osadchenko I, Kovalenko T, Yamada C, Chereshynska A, Smozhanyk K, Ostrovska G, Groppa S, Movila A, Skibo G. Maternal antibiotic administration during gestation can affect the memory and brain structure in mouse offspring. Front Cell Neurosci 2023; 17:1176676. [PMID: 37234915 PMCID: PMC10206017 DOI: 10.3389/fncel.2023.1176676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/18/2023] [Indexed: 05/28/2023] Open
Abstract
Maternal antibiotics administration (MAA) is among the widely used therapeutic approaches in pregnancy. Although published evidence demonstrates that infants exposed to antibiotics immediately after birth have altered recognition memory responses at one month of age, very little is known about in utero effects of antibiotics on the neuronal function and behavior of children after birth. Therefore, this study aimed to evaluate the impact of MAA at different periods of pregnancy on memory decline and brain structural alterations in young mouse offspring after their first month of life. To study the effects of MAA on 4-week-old offspring, pregnant C57BL/6J mouse dams (2-3-month-old; n = 4/group) were exposed to a cocktail of amoxicillin (205 mg/kg/day) and azithromycin (51 mg/kg/day) in sterile drinking water (daily/1 week) during either the 2nd or 3rd week of pregnancy and stopped after delivery. A control group of pregnant dams was exposed to sterile drinking water alone during all three weeks of pregnancy. Then, the 4-week-old offspring mice were first evaluated for behavioral changes. Using the Morris water maze assay, we revealed that exposure of pregnant mice to antibiotics at the 2nd and 3rd weeks of pregnancy significantly altered spatial reference memory and learning skills in their offspring compared to those delivered from the control group of dams. In contrast, no significant difference in long-term associative memory was detected between offspring groups using the novel object recognition test. Then, we histologically evaluated brain samples from the same offspring individuals using conventional immunofluorescence and electron microscopy assays. To our knowledge, we observed a reduction in the density of the hippocampal CA1 pyramidal neurons and hypomyelination in the corpus callosum in groups of mice in utero exposed to antibiotics at the 2nd and 3rd weeks of gestation. In addition, offspring exposed to antibiotics at the 2nd or 3rd week of gestation demonstrated a decreased astrocyte cell surface area and astrocyte territories or depletion of neurogenesis in the dentate gyrus and hippocampal synaptic loss, respectively. Altogether, this study shows that MAA at different times of pregnancy can pathologically alter cognitive behavior and brain development in offspring at an early age after weaning.
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Affiliation(s)
- Dmytro Shepilov
- Department of Cytology, Bogomoletz Institute of Physiology, NAS of Ukraine, Kyiv, Ukraine
| | - Iryna Osadchenko
- Department of Cytology, Bogomoletz Institute of Physiology, NAS of Ukraine, Kyiv, Ukraine
| | - Tetiana Kovalenko
- Department of Cytology, Bogomoletz Institute of Physiology, NAS of Ukraine, Kyiv, Ukraine
| | - Chiaki Yamada
- Department of Biomedical Sciences and Comprehensive Care, School of Dentistry, Indiana University, Indianapolis, IN, United States
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Anastasiia Chereshynska
- Department of Biomedical Sciences and Comprehensive Care, School of Dentistry, Indiana University, Indianapolis, IN, United States
| | - Kateryna Smozhanyk
- Department of Cytology, Bogomoletz Institute of Physiology, NAS of Ukraine, Kyiv, Ukraine
| | - Galyna Ostrovska
- Department of Cytology, Histology, and Reproductive Medicine, Institute of Biology and Medicine, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
| | - Stanislav Groppa
- Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldova
- Department of Neurology, State University of Medicine and Pharmacy “Nicolae Testemiţanu”, Chisinau, Moldova
| | - Alexandru Movila
- Department of Biomedical Sciences and Comprehensive Care, School of Dentistry, Indiana University, Indianapolis, IN, United States
- Indiana Center for Musculoskeletal Health, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Galyna Skibo
- Department of Cytology, Bogomoletz Institute of Physiology, NAS of Ukraine, Kyiv, Ukraine
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Paquola C, Hong SJ. The Potential of Myelin-Sensitive Imaging: Redefining Spatiotemporal Patterns of Myeloarchitecture. Biol Psychiatry 2023; 93:442-454. [PMID: 36481065 DOI: 10.1016/j.biopsych.2022.08.031] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/12/2022] [Accepted: 08/30/2022] [Indexed: 02/07/2023]
Abstract
Recent advances in magnetic resonance imaging (MRI) have paved the way for approximation of myelin content in vivo. In this review, our main goal was to determine how to best capitalize on myelin-sensitive imaging. First, we briefly overview the theoretical and empirical basis for the myelin sensitivity of different MRI markers and, in doing so, highlight how multimodal imaging approaches are important for enhancing specificity to myelin. Then, we discuss recent studies that have probed the nonuniform distribution of myelin across cortical layers and along white matter tracts. These approaches, collectively known as myelin profiling, have provided detailed depictions of myeloarchitecture in both the postmortem and living human brain. Notably, MRI-based profiling studies have recently focused on investigating whether it can capture interindividual variability in myelin characteristics as well as trajectories across the lifespan. Finally, another line of recent evidence emphasizes the contribution of region-specific myelination to large-scale organization, demonstrating the impact of myelination on global brain networks. In conclusion, we suggest that combining well-validated MRI markers with profiling techniques holds strong potential to elucidate individual differences in myeloarchitecture, which has important implications for understanding brain function and disease.
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Affiliation(s)
- Casey Paquola
- Institute of Neuroscience and Medicine, Forschungszentrum Jülich, Jülich, Germany.
| | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Suwon, South Korea; Center for the Developing Brain, Child Mind Institute, New York, New York; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
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7
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Moinian S, Vegh V, Reutens D. Towards automated in vivo parcellation of the human cerebral cortex using supervised classification of magnetic resonance fingerprinting residuals. Cereb Cortex 2023; 33:1550-1565. [PMID: 35483706 PMCID: PMC9977388 DOI: 10.1093/cercor/bhac155] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 03/29/2022] [Accepted: 03/30/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Accurate parcellation of the cerebral cortex in an individual is a guide to its underlying organization. The most promising in vivo quantitative magnetic resonance (MR)-based microstructural cortical mapping methods are yet to achieve a level of parcellation accuracy comparable to quantitative histology. METHODS We scanned 6 participants using a 3D echo-planar imaging MR fingerprinting (EPI-MRF) sequence on a 7T Siemens scanner. After projecting MRF signals to the individual-specific inflated model of the cortical surface, normalized autocorrelations of MRF residuals of vertices of 8 microstructurally distinct areas (BA1, BA2, BA4a, BA6, BA44, BA45, BA17, and BA18) from 3 cortical regions were used as feature vector inputs into linear support vector machine (SVM), radial basis function SVM (RBF-SVM), random forest, and k-nearest neighbors supervised classification algorithms. The algorithms' prediction performance was compared using: (i) features from each vertex or (ii) features from neighboring vertices. RESULTS The neighborhood-based RBF-SVM classifier achieved the highest prediction score of 0.85 for classification of MRF residuals in the central region from a held-out participant. CONCLUSIONS We developed an automated method of cortical parcellation using a combination of MR fingerprinting residual analysis and machine learning classification. Our findings provide the basis for employing unsupervised learning algorithms for whole-cortex structural parcellation in individuals.
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Affiliation(s)
- Shahrzad Moinian
- Centre for Advanced Imaging, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia.,ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia
| | - Viktor Vegh
- Centre for Advanced Imaging, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia.,ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia
| | - David Reutens
- Centre for Advanced Imaging, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia.,ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia
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8
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Berg RC, Menegaux A, Amthor T, Gilbert G, Mora M, Schlaeger S, Pongratz V, Lauerer M, Sorg C, Doneva M, Vavasour I, Mühlau M, Preibisch C. Comparing myelin-sensitive magnetic resonance imaging measures and resulting g-ratios in healthy and multiple sclerosis brains. Neuroimage 2022; 264:119750. [PMID: 36379421 PMCID: PMC9931395 DOI: 10.1016/j.neuroimage.2022.119750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/11/2022] [Accepted: 11/11/2022] [Indexed: 11/15/2022] Open
Abstract
The myelin concentration and the degree of myelination of nerve fibers can provide valuable information on the integrity of human brain tissue. Magnetic resonance imaging (MRI) of myelin-sensitive parameters can help to non-invasively evaluate demyelinating diseases such as multiple sclerosis (MS). Several different myelin-sensitive MRI methods have been proposed to determine measures of the degree of myelination, in particular the g-ratio. However, variability in underlying physical principles and different biological models influence measured myelin concentrations, and consequently g-ratio values. We therefore investigated similarities and differences between five different myelin-sensitive MRI measures and their effects on g-ratio mapping in the brains of both MS patients and healthy volunteers. We compared two different estimates of the myelin water fraction (MWF) as well as the inhomogeneous magnetization transfer ratio (ihMTR), magnetization transfer saturation (MTsat), and macromolecular tissue volume (MTV) in 13 patients with MS and 14 healthy controls. In combination with diffusion-weighted imaging, we derived g-ratio parameter maps for each of the five different myelin measures. The g-ratio values calculated from different myelin measures varied strongly, especially in MS lesions. While, compared to normal-appearing white matter, MTsat and one estimate of the MWF resulted in higher g-ratio values within lesions, ihMTR, MTV, and the second MWF estimate resulted in lower lesion g-ratio values. As myelin-sensitive measures provide rough estimates of myelin content rather than absolute myelin concentrations, resulting g-ratio values strongly depend on the utilized myelin measure and model used for g-ratio mapping. When comparing g-ratio values, it is, thus, important to utilize the same MRI methods and models or to consider methodological differences. Particular caution is necessary in pathological tissue such as MS lesions.
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Affiliation(s)
- Ronja C. Berg
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Corresponding author at: Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaninger Str. 22, 81675, München, Germany. (R.C. Berg)
| | - Aurore Menegaux
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | | | | | - Maria Mora
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany
| | - Sarah Schlaeger
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany
| | - Viola Pongratz
- Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | - Markus Lauerer
- Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | - Christian Sorg
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany,Technical University of Munich, School of Medicine, Department of Psychiatry, Munich, Germany
| | | | - Irene Vavasour
- University of British Columbia, Department of Radiology, Vancouver, BC, Canada
| | - Mark Mühlau
- Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany,Technical University of Munich, School of Medicine, Department of Neurology, Munich, Germany,Technical University of Munich, School of Medicine, TUM Neuroimaging Center, Munich, Germany
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9
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York EN, Meijboom R, Thrippleton MJ, Bastin ME, Kampaite A, White N, Chandran S, Waldman AD. Longitudinal microstructural MRI markers of demyelination and neurodegeneration in early relapsing-remitting multiple sclerosis: Magnetisation transfer, water diffusion and g-ratio. Neuroimage Clin 2022; 36:103228. [PMID: 36265199 PMCID: PMC9668599 DOI: 10.1016/j.nicl.2022.103228] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 10/07/2022] [Accepted: 10/08/2022] [Indexed: 11/11/2022]
Abstract
INTRODUCTION Quantitative microstructural MRI, such as myelin-sensitive magnetisation transfer ratio (MTR) or saturation (MTsat), axon-sensitive water diffusion Neurite Orientation Dispersion and Density Imaging (NODDI), and the aggregate g-ratio, may provide more specific markers of white matter integrity than conventional MRI for early patient stratification in relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to determine the sensitivity of such markers to longitudinal pathological change within cerebral white matter lesions (WML) and normal-appearing white matter (NAWM) in recently diagnosed RRMS. METHODS Seventy-nine people with recently diagnosed RRMS, from the FutureMS longitudinal cohort, were recruited to an extended MRI protocol at baseline and one year later. Twelve healthy volunteers received the same MRI protocol, repeated within two weeks. Ethics approval and written informed consent were obtained. 3T MRI included magnetisation transfer, and multi-shell diffusion-weighted imaging. NAWM and whole brain were segmented from 3D T1-weighted MPRAGE, and WML from T2-weighted FLAIR. MTR, MTsat, NODDI isotropic (ISOVF) and intracellular (ICVF) volume fractions, and g-ratio (calculated from MTsat and NODDI data) were measured within WML and NAWM. Brain parenchymal fraction (BPF) was also calculated. Longitudinal change in BPF and microstructural metrics was assessed with paired t-tests (α = 0.05) and linear mixed models, adjusted for confounding factors with False Discovery Rate (FDR) correction for multiple comparisons. Longitudinal changes were compared with test-retest Bland-Altman limits of agreement from healthy control white matter. The influence of longitudinal change on g-ratio was explored through post-hoc analysis in silico by computing g-ratio with realistic simulated MTsat and NODDI values. RESULTS In NAWM, g-ratio and ICVF increased, and MTsat decreased over one year (adjusted mean difference = 0.007, 0.005, and -0.057 respectively, all FDR-corrected p < 0.05). There was no significant change in MTR, ISOVF, or BPF. In WML, MTsat, NODDI ICVF and ISOVF increased over time (adjusted mean difference = 0.083, 0.024 and 0.016, respectively, all FDR-corrected p < 0.05). Group-level longitudinal changes exceeded test-retest limits of agreement for NODDI ISOVF and ICVF in WML only. In silico analysis showed g-ratio may increase due to a decrease in MTsat or ISOVF, or an increase in ICVF. DISCUSSION G-ratio and MTsat changes in NAWM over one year may indicate subtle myelin loss in early RRMS, which were not apparent with BPF or NAWM MTR. Increases in NAWM and WML NODDI ICVF were not anticipated, and raise the possibility of axonal swelling or morphological change. Increases in WML MTsat may reflect myelin repair. Changes in NODDI ISOVF are more likely to reflect alterations in water content. Competing MTsat and ICVF changes may account for the absence of g-ratio change in WML. Longitudinal changes in microstructural measures are significant at a group level, however detection in individual patients in early RRMS is limited by technique reproducibility. CONCLUSION MTsat and g-ratio are more sensitive than MTR to early pathological changes in RRMS, but complex dependence of g-ratio on NODDI parameters limit the interpretation of aggregate measures in isolation. Improvements in technique reproducibility and validation of MRI biophysical models across a range of pathological tissue states are needed.
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Affiliation(s)
- Elizabeth N York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom; Anne Rowling Regenerative Neurology Clinic, Edinburgh, United Kingdom.
| | - Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicole White
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Anne Rowling Regenerative Neurology Clinic, Edinburgh, United Kingdom; UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Adam D Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom.
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10
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Clark IA, Mohammadi S, Callaghan MF, Maguire EA. Conduction velocity along a key white matter tract is associated with autobiographical memory recall ability. eLife 2022; 11:79303. [PMID: 36166372 PMCID: PMC9514844 DOI: 10.7554/elife.79303] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 09/12/2022] [Indexed: 12/01/2022] Open
Abstract
Conduction velocity is the speed at which electrical signals travel along axons and is a crucial determinant of neural communication. Inferences about conduction velocity can now be made in vivo in humans using a measure called the magnetic resonance (MR) g-ratio. This is the ratio of the inner axon diameter relative to that of the axon plus the myelin sheath that encases it. Here, in the first application to cognition, we found that variations in MR g-ratio, and by inference conduction velocity, of the parahippocampal cingulum bundle were associated with autobiographical memory recall ability in 217 healthy adults. This tract connects the hippocampus with a range of other brain areas. We further observed that the association seemed to be with inner axon diameter rather than myelin content. The extent to which neurites were coherently organised within the parahippocampal cingulum bundle was also linked with autobiographical memory recall ability. Moreover, these findings were specific to autobiographical memory recall and were not apparent for laboratory-based memory tests. Our results offer a new perspective on individual differences in autobiographical memory recall ability, highlighting the possible influence of specific white matter microstructure features on conduction velocity when recalling detailed memories of real-life past experiences.
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Affiliation(s)
- Ian A Clark
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Siawoosh Mohammadi
- Institute of Systems Neuroscience, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Eleanor A Maguire
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
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11
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Piredda GF, Hilbert T, Ravano V, Canales-Rodríguez EJ, Pizzolato M, Meuli R, Thiran JP, Richiardi J, Kober T. Data-driven myelin water imaging based on T 1 and T 2 relaxometry. NMR IN BIOMEDICINE 2022; 35:e4668. [PMID: 34936147 DOI: 10.1002/nbm.4668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 11/16/2021] [Accepted: 11/30/2021] [Indexed: 06/14/2023]
Abstract
Long acquisition times preclude the application of multiecho spin echo (MESE) sequences for myelin water fraction (MWF) mapping in daily clinical practice. In search of alternative methods, previous studies of interest explored the biophysical modeling of MWF from measurements of different tissue properties that can be obtained in scan times shorter than those required for the MESE. In this work, a novel data-driven estimation of MWF maps from fast relaxometry measurements is proposed and investigated. T1 and T2 relaxometry maps were acquired in a cohort of 20 healthy subjects along with a conventional MESE sequence. Whole-brain quantitative mapping was achieved with a fast protocol in 6 min 24 s. Reference MWF maps were derived from the MESE sequence (TA = 11 min 17 s) and their data-driven estimation from relaxometry measurements was investigated using three different modeling strategies: two general linear models (GLMs) with linear and quadratic regressors, respectively; a random forest regression model; and two deep neural network architectures, a U-Net and a conditional generative adversarial network (cGAN). Models were validated using a 10-fold crossvalidation. The resulting maps were visually and quantitatively compared by computing the root mean squared error (RMSE) between the estimated and reference MWF maps, the intraclass correlation coefficients (ICCs) between corresponding MWF values in different brain regions, and by performing Bland-Altman analysis. Qualitatively, the estimated maps appear to generally provide a similar, yet more blurred MWF contrast in comparison with the reference, with the cGAN model best capturing MWF variabilities in small structures. By estimating the average adjusted coefficient of determination of the GLM with quadratic regressors, we showed that 87% of the variability in the MWF values can be explained by relaxation times alone. Further quantitative analysis showed an average RMSE smaller than 0.1% for all methods. The ICC was greater than 0.81 for all methods, and the bias smaller than 2.19%. It was concluded that this work confirms the notion that relaxometry parameters contain a large part of the information on myelin water and that MWF maps can be generated from T1 /T2 data with minimal error. Among the investigated modeling approaches, the cGAN provided maps with the best trade-off between accuracy and blurriness. Fast relaxometry, like the 6 min 24 s whole-brain protocol used in this work in conjunction with machine learning, may thus have the potential to replace time-consuming MESE acquisitions.
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Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | | | - Marco Pizzolato
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Reto Meuli
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jonas Richiardi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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12
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Oliveira R, Pelentritou A, Di Domenicantonio G, De Lucia M, Lutti A. In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data. Front Neurosci 2022; 16:874023. [PMID: 35527816 PMCID: PMC9070985 DOI: 10.3389/fnins.2022.874023] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 03/24/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose We present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired in vivo in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity. Theory The proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [P(r)] and (2) the g-ratio of the individual axons that compose this tract [g(r)]. P(r) is assumed to follow a Gamma distribution with mode and scale parameters, M and θ, and g(r) is described by a power law with parameters α and β. Methods MRI and EEG data were recorded from 14 healthy volunteers. MRI data were collected with a 3T scanner. MRI-measured g-ratio maps were computed and sampled along the visual transcallosal tract. EEG data were recorded using a 128-lead system with a visual Poffenberg paradigm. The interhemispheric transfer time and axonal conduction velocity were computed from the EEG current density at the group level. Using the MRI and EEG measures and the proposed model, we estimated morphological properties of axons in the visual transcallosal tract. Results The estimated interhemispheric transfer time was 11.72 ± 2.87 ms, leading to an average conduction velocity across subjects of 13.22 ± 1.18 m/s. Out of the 4 free parameters of the proposed model, we estimated θ – the width of the right tail of the axonal radius distribution – and β – the scaling factor of the axonal g-ratio, a measure of fiber myelination. Across subjects, the parameter θ was 0.40 ± 0.07 μm and the parameter β was 0.67 ± 0.02 μm−α. Conclusion The estimates of axonal radius and myelination are consistent with histological findings, illustrating the feasibility of this approach. The proposed method allows the measurement of the distribution of axonal radius and myelination within a white matter tract, opening new avenues for the combined study of brain structure and function, and for in vivo histological studies of the human brain.
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13
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Schiavi S, Lu PJ, Weigel M, Lutti A, Jones DK, Kappos L, Granziera C, Daducci A. Bundle myelin fraction (BMF) mapping of different white matter connections using microstructure informed tractography. Neuroimage 2022; 249:118922. [PMID: 35063648 PMCID: PMC7615247 DOI: 10.1016/j.neuroimage.2022.118922] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 01/13/2022] [Accepted: 01/17/2022] [Indexed: 12/13/2022] Open
Abstract
To date, we have scarce information about the relative myelination level of different fiber bundles in the human brain. Indirect evidence comes from postmortem histology data but histological stainings are unable to follow a specific bundle and determine its intrinsic myelination. In this context, quantitative MRI, and diffusion MRI tractography may offer a viable solution by providing, respectively, voxel-wise myelin sensitive maps and the pathways of the major tracts of the brain. Then, "tractometry" can be used to combine these two pieces of information by averaging tissue features (obtained from any voxel-wise map) along the streamlines recovered with diffusion tractography. Although this method has been widely used in the literature, in cases of voxels containing multiple fiber populations (each with different levels of myelination), tractometry provides biased results because the same value will be attributed to any bundle passing through the voxel. To overcome this bias, we propose a new method - named "myelin streamline decomposition" (MySD) - which extends convex optimization modeling for microstructure informed tractography (COMMIT) allowing the actual value measured by a microstructural map to be deconvolved on each individual streamline, thereby recovering unique bundle-specific myelin fractions (BMFs). We demonstrate the advantage of our method with respect to tractometry in well-studied bundles and compare the cortical projection of the obtained bundle-wise myelin values of both methods. We also prove the stability of our approach across different subjects and different MRI sensitive myelin mapping approaches. This work provides a proof-of-concept of in vivo investigations of entire neuronal pathways that, to date, are not possible.
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Affiliation(s)
- Simona Schiavi
- Department of Computer Science, University of Verona, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Italy.
| | - Po-Jui Lu
- Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Radiological Physics, Department of Radiology, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre, Cardiff University, United Kingdom; Neuroscience and Mental Health Research Institute, Cardiff University, United Kingdom
| | - Ludwig Kappos
- Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
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14
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Hori M, Maekawa T, Kamiya K, Hagiwara A, Goto M, Takemura MY, Fujita S, Andica C, Kamagata K, Cohen-Adad J, Aoki S. Advanced Diffusion MR Imaging for Multiple Sclerosis in the Brain and Spinal Cord. Magn Reson Med Sci 2022; 21:58-70. [PMID: 35173096 PMCID: PMC9199983 DOI: 10.2463/mrms.rev.2021-0091] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Diffusion tensor imaging (DTI) has been established its usefulness in evaluating normal-appearing white matter (NAWM) and other lesions that are difficult to evaluate with routine clinical MRI in the evaluation of the brain and spinal cord lesions in multiple sclerosis (MS), a demyelinating disease. With the recent advances in the software and hardware of MRI systems, increasingly complex and sophisticated MRI and analysis methods, such as q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, white matter tract integrity, and multiple diffusion encoding, referred to as advanced diffusion MRI, have been proposed. These are capable of capturing in vivo microstructural changes in the brain and spinal cord in normal and pathological states in greater detail than DTI. This paper reviews the current status of recent advanced diffusion MRI for assessing MS in vivo as part of an issue celebrating two decades of magnetic resonance in medical sciences (MRMS), an official journal of the Japanese Society of Magnetic Resonance in Medicine.
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Affiliation(s)
- Masaaki Hori
- Department of Radiology, Toho University Omori Medical Center.,Department of Radiology, Juntendo University School of Medicine
| | - Tomoko Maekawa
- Department of Radiology, Juntendo University School of Medicine
| | - Kouhei Kamiya
- Department of Radiology, Toho University Omori Medical Center.,Department of Radiology, Juntendo University School of Medicine
| | | | - Masami Goto
- Department of Radiological Technology, Faculty of Health Science, Juntendo University
| | | | - Shohei Fujita
- Department of Radiology, Juntendo University School of Medicine
| | | | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine
| | | | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine
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15
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Cortina LE, Kim RW, Kiely M, Triebswetter C, Gong Z, Alsameen MH, Bouhrara M. Cerebral aggregate g-ratio mapping using magnetic resonance relaxometry and diffusion tensor imaging to investigate sex and age-related differences in white matter microstructure. Magn Reson Imaging 2022; 85:87-92. [PMID: 34678436 PMCID: PMC8629921 DOI: 10.1016/j.mri.2021.10.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 10/15/2021] [Accepted: 10/16/2021] [Indexed: 01/03/2023]
Abstract
Axonal demyelination is a cardinal feature of aging and age-related diseases. The g-ratio, mathematically defined as the inner-to-outer diameter of a myelinated axon, is used as a structural index of optimal axonal myelination and has been shown to represent a sensitive imaging biomarker of microstructural integrity. Several magnetic resonance imaging (MRI) methods for whole-brain mapping of aggregate g-ratio have been introduced. Computation of the aggerate g-ratio requires estimates of the myelin volume fraction (MVF) and the axonal volume fraction (AVF). While accurate determinations of MVF and AVF can be obtained through multicomponent relaxometry or diffusion analyses, respectively, these methods require lengthy acquisition times making their implementation challenging in a clinical context. Therefore, any attempt to overcome this drawback is needed. Expanding on our previous work, we introduced a new MRI method for whole-brain mapping of aggregate g-ratio. This new approach is based on the use of a single-shell diffusion for AVF determination, reducing the acquisition time by approximately ~10 min from our recently introduced approach, while offering the possibility to investigate g-ratio differences in previous studies with existing data for MVF mapping and single-shell diffusion data for AVF mapping. Our comparison analysis indicates that our newly derived aggregate g-ratio values were similar to those derived from our previous method, which requires a longer acquisition time. Further, in agreement with our previous observations, we found quadratic U-shaped relationships between aggregate g-ratio and age in this much larger study cohort. However, our results show that sexual dimorphism in g-ratio was not significant in any brain region investigated.
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Affiliation(s)
| | | | | | | | | | | | - Mustapha Bouhrara
- Corresponding author: Mustapha Bouhrara, PhD., MRPAD Unit, National Institute on Aging (NIA), National Institutes of Health (NIH), Intramural Research Program, BRC 05C-222, 251 Bayview Boulevard, Baltimore, MD 21224, USA. Tel: 410-558-8541,
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16
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Meijboom R, Wiseman SJ, York EN, Bastin ME, Valdés Hernández MDC, Thrippleton MJ, Mollison D, White N, Kampaite A, Ng Kee Kwong K, Rodriguez Gonzalez D, Job D, Weaver C, Kearns PKA, Connick P, Chandran S, Waldman AD. Rationale and design of the brain magnetic resonance imaging protocol for FutureMS: a longitudinal multi-centre study of newly diagnosed patients with relapsing-remitting multiple sclerosis in Scotland. Wellcome Open Res 2022; 7:94. [PMID: 36865371 PMCID: PMC9971644 DOI: 10.12688/wellcomeopenres.17731.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/02/2022] [Indexed: 12/22/2022] Open
Abstract
Introduction: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease. MS prevalence varies geographically and is notably high in Scotland. Disease trajectory varies significantly between individuals and the causes for this are largely unclear. Biomarkers predictive of disease course are urgently needed to allow improved stratification for current disease modifying therapies and future targeted treatments aimed at neuroprotection and remyelination. Magnetic resonance imaging (MRI) can detect disease activity and underlying damage non-invasively in vivo at the micro and macrostructural level. FutureMS is a prospective Scottish longitudinal multi-centre cohort study, which focuses on deeply phenotyping patients with recently diagnosed relapsing-remitting MS (RRMS). Neuroimaging is a central component of the study and provides two main primary endpoints for disease activity and neurodegeneration. This paper provides an overview of MRI data acquisition, management and processing in FutureMS. FutureMS is registered with the Integrated Research Application System (IRAS, UK) under reference number 169955. Methods and analysis: MRI is performed at baseline (N=431) and 1-year follow-up, in Dundee, Glasgow and Edinburgh (3T Siemens) and in Aberdeen (3T Philips), and managed and processed in Edinburgh. The core structural MRI protocol comprises T1-weighted, T2-weighted, FLAIR and proton density images. Primary imaging outcome measures are new/enlarging white matter lesions (WML) and reduction in brain volume over one year. Secondary imaging outcome measures comprise WML volume as an additional quantitative structural MRI measure, rim lesions on susceptibility-weighted imaging, and microstructural MRI measures, including diffusion tensor imaging and neurite orientation dispersion and density imaging metrics, relaxometry, magnetisation transfer (MT) ratio, MT saturation and derived g-ratio measures. Conclusions: FutureMS aims to reduce uncertainty around disease course and allow for targeted treatment in RRMS by exploring the role of conventional and advanced MRI measures as biomarkers of disease severity and progression in a large population of RRMS patients in Scotland.
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Affiliation(s)
- Rozanna Meijboom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Stewart J. Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Elizabeth N. York
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Mark E. Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Maria del C. Valdés Hernández
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Michael J. Thrippleton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Daisy Mollison
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Nicole White
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Agniete Kampaite
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Koy Ng Kee Kwong
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - David Rodriguez Gonzalez
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Dominic Job
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
| | - Christine Weaver
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Patrick K. A. Kearns
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Siddharthan Chandran
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
| | - Adam D. Waldman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
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17
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Assessing the differential sensitivities of wave-CAIPI ViSTa myelin water fraction and magnetization transfer saturation for efficiently quantifying tissue damage in MS. Mult Scler Relat Disord 2021; 56:103309. [PMID: 34688179 DOI: 10.1016/j.msard.2021.103309] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 09/21/2021] [Accepted: 10/02/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND Wave-CAIPI Visualization of Short Transverse relaxation time component (ViSTa) is a recently developed, short-T1-sensitized MRI method for fast quantification of myelin water fraction (MWF) in the human brain. It represents a promising technique for the evaluation of subtle, early signals of demyelination in the cerebral white matter of multiple sclerosis (MS) patients. Currently however, few studies exist that robustly assess the utility of ViSTa MWF measures of myelin compared to more conventional MRI measures of myelin in the brain of MS patients. Moreover, there are no previous studies evaluating the sensitivity of ViSTa MWF for the non-invasive detection of subtle tissue damage in both normal-appearing white matter (NAWM) and white matter lesions of MS patients. As a result, a central purpose of this study was to systematically evaluate the relationship between myelin sensitivity of T1-based ViSTa MWF mapping and a more generally recognized metric, Magnetization Transfer Saturation (MTsat), in healthy control and MS brain white matter. METHODS ViSTa MWF and MTsat values were evaluated in automatically-classified normal appearing white matter (NAWM), white matter (WM) lesion tissue, cortical gray matter, and deep gray matter of 29 MS patients and 10 healthy controls using 3T MRI. MWF and MT sat were also assessed in a tract-specific manner using the Johns Hopkins University WM atlas. MRI-derived measures of cerebral myelin content were uniquely compared by employing non-normal distribution-specific measures of median, interquartile range and skewness. Separate analyses of variance were applied to test tissue-specific differences in MTsat and ViSTa MWF distribution metrics. Non-parametric tests were utilized when appropriate. All tests were corrected for multiple comparisons using the False Discovery Rate method at the level, α=0.05. RESULTS Differences in whole NAWM MS tissue damage were detected with a higher effect size when using ViSTa MWF (q = 0.0008; ƞ2 = 0.34) compared to MTsat (q = 0.02; ƞ2= 0.24). We also observed that, as a possible measure of WM pathology, ViSTa-derived NAWM MWF voxel distributions of MS subjects were consistently skewed towards lower MWF values, while MTsat voxel distributions showed reduced skewness values. We further identified tract-specific reductions in mean ViSTa MWF of MS patients compared to controls that were not observed with MTsat. However, MTsat (q = 1.4 × 10-21; ƞ2 = 0.88) displayed higher effect sizes when differentiating NAWM and MS lesion tissue. Using regression analysis at the group level, we identified a linear relationship between MTsat and ViSTa MWF in NAWM (R2 = 0.46; p = 7.8 × 10-4) lesions (R2 = 0.30; p = 0.004), and with all tissue types combined (R2 = 0.71; p = 8.4 × 10-45). The linear relationship was also observed in most of the WM tracts we investigated. ViSTa MWF in NAWM of MS patients correlated with both disease duration (p = 0.02; R2 = 0.27) and WM lesion volume (p = 0.002; R2 = 0.34). CONCLUSION Because ViSTa MWF and MTsat metrics exhibit differential sensitivities to tissue damage in MS white matter, they can be collected in combination to provide an efficient, comprehensive measure of myelin water and macromolecular pool proton signals. These complementary measures may offer a more sensitive, non-invasive biopsy of early precursor signals in NAWM that occur prior to lesion formation. They may also aid in monitoring the efficacy of remyelination therapies.
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18
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Clark IA, Callaghan MF, Weiskopf N, Maguire EA, Mohammadi S. Reducing Susceptibility Distortion Related Image Blurring in Diffusion MRI EPI Data. Front Neurosci 2021; 15:706473. [PMID: 34421526 PMCID: PMC8376472 DOI: 10.3389/fnins.2021.706473] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 07/09/2021] [Indexed: 11/21/2022] Open
Abstract
Diffusion magnetic resonance imaging (MRI) is an increasingly popular technique in basic and clinical neuroscience. One promising application is to combine diffusion MRI with myelin maps from complementary MRI techniques such as multi-parameter mapping (MPM) to produce g-ratio maps that represent the relative myelination of axons and predict their conduction velocity. Statistical Parametric Mapping (SPM) can process both diffusion data and MPMs, making SPM the only widely accessible software that contains all the processing steps required to perform group analyses of g-ratio data in a common space. However, limitations have been identified in its method for reducing susceptibility-related distortion in diffusion data. More generally, susceptibility-related image distortion is often corrected by combining reverse phase-encoded images (blip-up and blip-down) using the arithmetic mean (AM), however, this can lead to blurred images. In this study we sought to (1) improve the susceptibility-related distortion correction for diffusion MRI data in SPM; (2) deploy an alternative approach to the AM to reduce image blurring in diffusion MRI data when combining blip-up and blip-down EPI data after susceptibility-related distortion correction; and (3) assess the benefits of these changes for g-ratio mapping. We found that the new processing pipeline, called consecutive Hyperelastic Susceptibility Artefact Correction (HySCO) improved distortion correction when compared to the standard approach in the ACID toolbox for SPM. Moreover, using a weighted average (WA) method to combine the distortion corrected data from each phase-encoding polarity achieved greater overlap of diffusion and more anatomically faithful structural white matter probability maps derived from minimally distorted multi-parameter maps as compared to the AM. Third, we showed that the consecutive HySCO WA performed better than the AM method when combined with multi-parameter maps to perform g-ratio mapping. These improvements mean that researchers can conveniently access a wide range of diffusion-related analysis methods within one framework because they are now available within the open-source ACID toolbox as part of SPM, which can be easily combined with other SPM toolboxes, such as the hMRI toolbox, to facilitate computation of myelin biomarkers that are necessary for g-ratio mapping.
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Affiliation(s)
- Ian A. Clark
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Nikolaus Weiskopf
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
- 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
| | - Eleanor A. Maguire
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Siawoosh Mohammadi
- Institute of Systems Neuroscience, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
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19
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Emmenegger TM, David G, Ashtarayeh M, Fritz FJ, Ellerbrock I, Helms G, Balteau E, Freund P, Mohammadi S. The Influence of Radio-Frequency Transmit Field Inhomogeneities on the Accuracy of G-ratio Weighted Imaging. Front Neurosci 2021; 15:674719. [PMID: 34290579 PMCID: PMC8287210 DOI: 10.3389/fnins.2021.674719] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 06/01/2021] [Indexed: 11/13/2022] Open
Abstract
G-ratio weighted imaging is a non-invasive, in-vivo MRI-based technique that aims at estimating an aggregated measure of relative myelination of axons across the entire brain white matter. The MR g-ratio and its constituents (axonal and myelin volume fraction) are more specific to the tissue microstructure than conventional MRI metrics targeting either the myelin or axonal compartment. To calculate the MR g-ratio, an MRI-based myelin-mapping technique is combined with an axon-sensitive MR technique (such as diffusion MRI). Correction for radio-frequency transmit (B1+) field inhomogeneities is crucial for myelin mapping techniques such as magnetization transfer saturation. Here we assessed the effect of B1+ correction on g-ratio weighted imaging. To this end, the B1+ field was measured and the B1+ corrected MR g-ratio was used as the reference in a Bland-Altman analysis. We found a substantial bias (≈-89%) and error (≈37%) relative to the dynamic range of g-ratio values in the white matter if the B1+ correction was not applied. Moreover, we tested the efficiency of a data-driven B1+ correction approach that was applied retrospectively without additional reference measurements. We found that it reduced the bias and error in the MR g-ratio by a factor of three. The data-driven correction is readily available in the open-source hMRI toolbox (www.hmri.info) which is embedded in the statistical parameter mapping (SPM) framework.
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Affiliation(s)
- Tim M Emmenegger
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gergely David
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Mohammad Ashtarayeh
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Francisco J Fritz
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Isabel Ellerbrock
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Gunther Helms
- Medical Radiation Physics, Clinical Sciences Lund (IKVL), Lund University, Lund, Sweden
| | | | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom
| | - Siawoosh Mohammadi
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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20
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Hédouin R, Metere R, Chan KS, Licht C, Mollink J, van Walsum AMC, Marques JP. Decoding the microstructural properties of white matter using realistic models. Neuroimage 2021; 237:118138. [PMID: 33964461 DOI: 10.1016/j.neuroimage.2021.118138] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2020] [Revised: 04/14/2021] [Accepted: 04/19/2021] [Indexed: 11/24/2022] Open
Abstract
Multi-echo gradient echo (ME-GRE) magnetic resonance signal evolution in white matter has a strong dependence on the orientation of myelinated axons with respect to the main static field. Although analytical solutions have been able to predict some of the white matter (WM) signal behaviour of the hollow cylinder model, it has been shown that realistic models of WM offer a better description of the signal behaviour observed. In this work, we present a pipeline to (i) generate realistic 2D WM models with their microstructure based on real axon morphology with adjustable fiber volume fraction (FVF) and g-ratio. We (ii) simulate their interaction with the static magnetic field to be able to simulate their MR signal. For the first time, we (iii) demonstrate that realistic 2D WM models can be used to simulate a MR signal that provides a good approximation of the signal obtained from a real 3D WM model derived from electron microscopy. We then (iv) demonstrate in silico that 2D WM models can be used to predict microstructural parameters in a robust way if ME-GRE multi-orientation data is available and the main fiber orientation in each pixel is known using DTI. A deep learning network was trained and characterized in its ability to recover the desired microstructural parameters such as FVF, g-ratio, free and bound water transverse relaxation and magnetic susceptibility. Finally, the network was trained to recover these micro-structural parameters from an ex vivo dataset acquired in 9 orientations with respect to the magnetic field and 12 echo times. We demonstrate that this is an overdetermined problem and that as few as 3 orientations can already provide comparable results for some of the decoded metrics.
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Affiliation(s)
- Renaud Hédouin
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands; Empenn, INRIA, INSERM, CNRS, Université de Rennes 1, Rennes, France.
| | - Riccardo Metere
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Kwok-Shing Chan
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Christian Licht
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Jeroen Mollink
- Radboud University Medical Centre, Medical Imaging and Anatomy, Nijmegen, Netherlands
| | | | - José P Marques
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
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21
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Ng AHM, Khoshakhlagh P, Rojo Arias JE, Pasquini G, Wang K, Swiersy A, Shipman SL, Appleton E, Kiaee K, Kohman RE, Vernet A, Dysart M, Leeper K, Saylor W, Huang JY, Graveline A, Taipale J, Hill DE, Vidal M, Melero-Martin JM, Busskamp V, Church GM. A comprehensive library of human transcription factors for cell fate engineering. Nat Biotechnol 2021; 39:510-519. [PMID: 33257861 PMCID: PMC7610615 DOI: 10.1038/s41587-020-0742-6] [Citation(s) in RCA: 93] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 10/19/2020] [Indexed: 02/06/2023]
Abstract
Human pluripotent stem cells (hPSCs) offer an unprecedented opportunity to model diverse cell types and tissues. To enable systematic exploration of the programming landscape mediated by transcription factors (TFs), we present the Human TFome, a comprehensive library containing 1,564 TF genes and 1,732 TF splice isoforms. By screening the library in three hPSC lines, we discovered 290 TFs, including 241 that were previously unreported, that induce differentiation in 4 days without alteration of external soluble or biomechanical cues. We used four of the hits to program hPSCs into neurons, fibroblasts, oligodendrocytes and vascular endothelial-like cells that have molecular and functional similarity to primary cells. Our cell-autonomous approach enabled parallel programming of hPSCs into multiple cell types simultaneously. We also demonstrated orthogonal programming by including oligodendrocyte-inducible hPSCs with unmodified hPSCs to generate cerebral organoids, which expedited in situ myelination. Large-scale combinatorial screening of the Human TFome will complement other strategies for cell engineering based on developmental biology and computational systems biology.
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Affiliation(s)
- Alex H M Ng
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
- GC Therapeutics, Inc, Cambridge, MA, USA
| | - Parastoo Khoshakhlagh
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
- GC Therapeutics, Inc, Cambridge, MA, USA
| | - Jesus Eduardo Rojo Arias
- Technische Universität Dresden, Center for Molecular and Cellular Bioengineering (CMCB), Center for Regenerative Therapies Dresden (CRTD), Dresden, Germany
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Giovanni Pasquini
- Technische Universität Dresden, Center for Molecular and Cellular Bioengineering (CMCB), Center for Regenerative Therapies Dresden (CRTD), Dresden, Germany
| | - Kai Wang
- Department of Cardiac Surgery, Boston Children's Hospital, Boston, MA, USA
- Department of Surgery, Harvard Medical School, Boston, MA, USA
| | - Anka Swiersy
- Technische Universität Dresden, Center for Molecular and Cellular Bioengineering (CMCB), Center for Regenerative Therapies Dresden (CRTD), Dresden, Germany
| | - Seth L Shipman
- Gladstone Institutes and University of California, San Francisco, San Francisco, CA, USA
| | - Evan Appleton
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
- GC Therapeutics, Inc, Cambridge, MA, USA
| | - Kiavash Kiaee
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
- GC Therapeutics, Inc, Cambridge, MA, USA
| | - Richie E Kohman
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
| | - Andyna Vernet
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
| | - Matthew Dysart
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
| | - Kathleen Leeper
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
| | - Wren Saylor
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
| | - Jeremy Y Huang
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
| | - Amanda Graveline
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA
| | - Jussi Taipale
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden
- Applied Tumor Genomics Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - David E Hill
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
| | - Marc Vidal
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
| | - Juan M Melero-Martin
- Department of Cardiac Surgery, Boston Children's Hospital, Boston, MA, USA
- Department of Surgery, Harvard Medical School, Boston, MA, USA
| | - Volker Busskamp
- Technische Universität Dresden, Center for Molecular and Cellular Bioengineering (CMCB), Center for Regenerative Therapies Dresden (CRTD), Dresden, Germany.
- Department of Ophthalmology, Medical Faculty, University of Bonn, Bonn, Germany.
| | - George M Church
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA.
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
- GC Therapeutics, Inc, Cambridge, MA, USA.
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22
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Howell B, Isbaine F, Willie JT, Opri E, Gross RE, De Hemptinne C, Starr PA, McIntyre CC, Miocinovic S. Image-based biophysical modeling predicts cortical potentials evoked with subthalamic deep brain stimulation. Brain Stimul 2021; 14:549-563. [PMID: 33757931 DOI: 10.1016/j.brs.2021.03.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Revised: 02/19/2021] [Accepted: 03/14/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Subthalamic deep brain stimulation (DBS) is an effective surgical treatment for Parkinson's disease and continues to advance technologically with an enormous parameter space. As such, in-silico DBS modeling systems have become common tools for research and development, but their underlying methods have yet to be standardized and validated. OBJECTIVE Evaluate the accuracy of patient-specific estimates of neural pathway activations in the subthalamic region against intracranial, cortical evoked potential (EP) recordings. METHODS Pathway activations were modeled in eleven patients using the latest advances in connectomic modeling of subthalamic DBS, focusing on the hyperdirect pathway (HDP) and corticospinal/bulbar tract (CSBT) for their relevance in human research studies. Correlations between pathway activations and respective EP amplitudes were quantified. RESULTS Good model performance required accurate lead localization and image fusions, as well as appropriate selection of fiber diameter in the biophysical model. While optimal model parameters varied across patients, good performance could be achieved using a global set of parameters that explained 60% and 73% of electrophysiologic activations of CSBT and HDP, respectively. Moreover, restricted models fit to only EP amplitudes of eight standard (monopolar and bipolar) electrode configurations were able to extrapolate variation in EP amplitudes across other directional electrode configurations and stimulation parameters, with no significant reduction in model performance across the cohort. CONCLUSIONS Our findings demonstrate that connectomic models of DBS with sufficient anatomical and electrical details can predict recruitment dynamics of white matter. These results will help to define connectomic modeling standards for preoperative surgical targeting and postoperative patient programming applications.
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Affiliation(s)
- Bryan Howell
- Department of Biomedical Engineering, Case Western Reserve University, USA
| | | | - Jon T Willie
- Department of Neurosurgery, Emory University, USA
| | - Enrico Opri
- Department of Neurology, Emory University, USA
| | | | | | - Philip A Starr
- Department of Neurological Surgery, University of California San Francisco, USA
| | - Cameron C McIntyre
- Department of Biomedical Engineering, Case Western Reserve University, USA
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23
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Bouhrara M, Kim RW, Khattar N, Qian W, Bergeron CM, Melvin D, Zukley LM, Ferrucci L, Resnick SM, Spencer RG. Age-related estimates of aggregate g-ratio of white matter structures assessed using quantitative magnetic resonance neuroimaging. Hum Brain Mapp 2021; 42:2362-2373. [PMID: 33595168 PMCID: PMC8090765 DOI: 10.1002/hbm.25372] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 01/21/2021] [Accepted: 02/04/2021] [Indexed: 12/19/2022] Open
Abstract
The g‐ratio, defined as the inner‐to‐outer diameter of a myelinated axon, is associated with the speed of nerve impulse conduction, and represents an index of axonal myelination and integrity. It has been shown to be a sensitive and specific biomarker of neurodevelopment and neurodegeneration. However, there have been very few magnetic resonance imaging studies of the g‐ratio in the context of normative aging; characterizing regional and time‐dependent cerebral changes in g‐ratio in cognitively normal subjects will be a crucial step in differentiating normal from abnormal microstructural alterations. In the current study, we investigated age‐related differences in aggregate g‐ratio, that is, g‐ratio averaged over all fibers within regions of interest, in several white matter regions in a cohort of 52 cognitively unimpaired participants ranging in age from 21 to 84 years. We found a quadratic, U‐shaped, relationship between aggregate g‐ratio and age in most cerebral regions investigated, suggesting myelin maturation until middle age followed by a decrease at older ages. As expected, we observed that these age‐related differences vary across different brain regions, with the frontal lobes and parietal lobes exhibiting slightly earlier ages of minimum aggregate g‐ratio as compared to more posterior structures such as the occipital lobes and temporal lobes; this agrees with the retrogenesis paradigm. Our results provide evidence for a nonlinear association between age and aggregate g‐ratio in a sample of adults from a highly controlled population. Finally, sex differences in aggregate g‐ratio were observed in several cerebral regions, with women exhibiting overall lower values as compared to men; this likely reflects the greater myelin content in women's brain, in agreement with recent investigations.
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Affiliation(s)
- Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Richard W Kim
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Nikkita Khattar
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Wenshu Qian
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Christopher M Bergeron
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Denise Melvin
- Clinical Research Core, Office of the Scientific Director, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Linda M Zukley
- Clinical Research Core, Office of the Scientific Director, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
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24
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Ozes B, Myers M, Moss K, Mckinney J, Ridgley A, Chen L, Bai S, Abrams CK, Freidin MM, Mendell JR, Sahenk Z. AAV1.NT-3 gene therapy for X-linked Charcot-Marie-Tooth neuropathy type 1. Gene Ther 2021; 29:127-137. [PMID: 33542455 PMCID: PMC9013664 DOI: 10.1038/s41434-021-00231-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 12/30/2020] [Accepted: 01/19/2021] [Indexed: 12/13/2022]
Abstract
X-linked Charcot-Marie-Tooth neuropathy (CMTX) is caused by mutations in the gene encoding Gap Junction Protein Beta-1 (GJB1)/Connexin32 (Cx32) in Schwann cells. Neurotrophin-3 (NT-3) is an important autocrine factor supporting Schwann cell survival and differentiation and stimulating axon regeneration and myelination. Improvements in these parameters have been shown previously in a CMT1 model, TremblerJ mouse, with NT-3 gene transfer therapy. For this study, scAAV1.tMCK.NT-3 was delivered to the gastrocnemius muscle of 3-month-old Cx32 knockout (KO) mice. Measurable levels of NT-3 were found in the serum at 6-month post gene delivery. The outcome measures included functional, electrophysiological and histological assessments. At 9-months of age, NT-3 treated mice showed no functional decline with normalized compound muscle action potential amplitudes. Myelin thickness and nerve conduction velocity significantly improved compared with untreated cohort. A normalization toward age-matched wildtype histopathological parameters included increased number of Schmidt-Lanterman incisures, and muscle fiber diameter. Collectively, these findings suggest a translational application to CMTX1.
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Affiliation(s)
- Burcak Ozes
- Center for Gene Therapy, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Morgan Myers
- Center for Gene Therapy, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Kyle Moss
- Center for Gene Therapy, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Jennifer Mckinney
- Department of Pediatrics and Neurology, Nationwide Children's Hospital and The Ohio State University, Columbus, OH, USA
| | - Alicia Ridgley
- Center for Gene Therapy, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Lei Chen
- Center for Gene Therapy, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Shasha Bai
- Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA.,Biostatistics Resource at Nationwide Children's Hospital, Columbus, OH, USA
| | - Charles K Abrams
- Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, USA
| | - Mona M Freidin
- Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, USA
| | - Jerry R Mendell
- Center for Gene Therapy, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics and Neurology, Nationwide Children's Hospital and The Ohio State University, Columbus, OH, USA
| | - Zarife Sahenk
- Center for Gene Therapy, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA. .,Department of Pediatrics and Neurology, Nationwide Children's Hospital and The Ohio State University, Columbus, OH, USA. .,Department of Pathology and Laboratory Medicine, Nationwide Children's Hospital, Columbus, OH, USA.
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25
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Yasaka K, Kamagata K, Ogawa T, Hatano T, Takeshige-Amano H, Ogaki K, Andica C, Akai H, Kunimatsu A, Uchida W, Hattori N, Aoki S, Abe O. Parkinson's disease: deep learning with a parameter-weighted structural connectome matrix for diagnosis and neural circuit disorder investigation. Neuroradiology 2021; 63:1451-1462. [PMID: 33481071 PMCID: PMC8376710 DOI: 10.1007/s00234-021-02648-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 01/12/2021] [Indexed: 12/22/2022]
Abstract
Purpose To investigate whether Parkinson’s disease (PD) can be differentiated from healthy controls and to identify neural circuit disorders in PD by applying a deep learning technique to parameter-weighted and number of streamlines (NOS)–based structural connectome matrices calculated from diffusion-weighted MRI. Methods In this prospective study, 115 PD patients and 115 healthy controls were enrolled. NOS-based and parameter-weighted connectome matrices were calculated from MRI images obtained with a 3-T MRI unit. With 5-fold cross-validation, diagnostic performance of convolutional neural network (CNN) models using those connectome matrices in differentiating patients with PD from healthy controls was evaluated. To identify the important brain connections for diagnosing PD, gradient-weighted class activation mapping (Grad-CAM) was applied to the trained CNN models. Results CNN models based on some parameter-weighted structural matrices (diffusion kurtosis imaging (DKI)–weighted, neurite orientation dispersion and density imaging (NODDI)–weighted, and g-ratio-weighted connectome matrices) showed moderate performance (areas under the receiver operating characteristic curve (AUCs) = 0.895, 0.801, and 0.836, respectively) in discriminating PD patients from healthy controls. The DKI-weighted connectome matrix performed significantly better than the conventional NOS-based matrix (AUC = 0.761) (DeLong’s test, p < 0.0001). Alterations of neural connections between the basal ganglia and cerebellum were indicated by applying Grad-CAM to the NODDI- and g-ratio-weighted matrices. Conclusion Patients with PD can be differentiated from healthy controls by applying the deep learning technique to the parameter-weighted connectome matrices, and neural circuit disorders including those between the basal ganglia on one side and the cerebellum on the contralateral side were visualized.
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Affiliation(s)
- Koichiro Yasaka
- Department of Radiology, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan.
| | - Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Takashi Ogawa
- Department of Neurology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Taku Hatano
- Department of Neurology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Haruka Takeshige-Amano
- Department of Neurology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Kotaro Ogaki
- Department of Neurology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Hiroyuki Akai
- Department of Radiology, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan
| | - Akira Kunimatsu
- Department of Radiology, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.,Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, 7-2-10 Higashi-Ogu, Arakawa-ku, 116-8551, Tokyo, Japan
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
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Mohammadi S, Callaghan MF. Towards in vivo g-ratio mapping using MRI: Unifying myelin and diffusion imaging. J Neurosci Methods 2021; 348:108990. [PMID: 33129894 PMCID: PMC7840525 DOI: 10.1016/j.jneumeth.2020.108990] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 09/21/2020] [Accepted: 10/20/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND The g-ratio, quantifying the comparative thickness of the myelin sheath encasing an axon, is a geometrical invariant that has high functional relevance because of its importance in determining neuronal conduction velocity. Advances in MRI data acquisition and signal modelling have put in vivo mapping of the g-ratio, across the entire white matter, within our reach. This capacity would greatly increase our knowledge of the nervous system: how it functions, and how it is impacted by disease. NEW METHOD This is the second review on the topic of g-ratio mapping using MRI. RESULTS This review summarizes the most recent developments in the field, while also providing methodological background pertinent to aggregate g-ratio weighted mapping, and discussing pitfalls associated with these approaches. COMPARISON WITH EXISTING METHODS Using simulations based on recently published data, this review reveals caveats to the state-of-the-art calibration methods that have been used for in vivo g-ratio mapping. It highlights the need to estimate both the slope and offset of the relationship between these MRI-based markers and the true myelin volume fraction if we are really to achieve the goal of precise, high sensitivity g-ratio mapping in vivo. Other challenges discussed in this review further evidence the need for gold standard measurements of human brain tissue from ex vivo histology. CONCLUSIONS We conclude that the quest to find the most appropriate MRI biomarkers to enable in vivo g-ratio mapping is ongoing, with the full potential of many novel techniques yet to be investigated.
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Affiliation(s)
- Siawoosh Mohammadi
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 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, UK
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Clark IA, Callaghan MF, Weiskopf N, Maguire EA. The relationship between hippocampal-dependent task performance and hippocampal grey matter myelination and iron content. Brain Neurosci Adv 2021; 5:23982128211011923. [PMID: 33997294 PMCID: PMC8079931 DOI: 10.1177/23982128211011923] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 04/01/2021] [Indexed: 02/02/2023] Open
Abstract
Individual differences in scene imagination, autobiographical memory recall, future thinking and spatial navigation have long been linked with hippocampal structure in healthy people, although evidence for such relationships is, in fact, mixed. Extant studies have predominantly concentrated on hippocampal volume. However, it is now possible to use quantitative neuroimaging techniques to model different properties of tissue microstructure in vivo such as myelination and iron. Previous work has linked such measures with cognitive task performance, particularly in older adults. Here we investigated whether performance on scene imagination, autobiographical memory, future thinking and spatial navigation tasks was associated with hippocampal grey matter myelination or iron content in young, healthy adult participants. Magnetic resonance imaging data were collected using a multi-parameter mapping protocol (0.8 mm isotropic voxels) from a large sample of 217 people with widely-varying cognitive task scores. We found little evidence that hippocampal grey matter myelination or iron content were related to task performance. This was the case using different analysis methods (voxel-based quantification, partial correlations), when whole brain, hippocampal regions of interest, and posterior:anterior hippocampal ratios were examined, and across different participant sub-groups (divided by gender and task performance). Variations in hippocampal grey matter myelin and iron levels may not, therefore, help to explain individual differences in performance on hippocampal-dependent tasks, at least in young, healthy individuals.
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Affiliation(s)
- Ian A. Clark
- Wellcome Centre for Human Neuroimaging,
UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging,
UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Nikolaus Weiskopf
- Wellcome Centre for Human Neuroimaging,
UCL Queen Square Institute of Neurology, University College London, London, UK
- 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
| | - Eleanor A. Maguire
- Wellcome Centre for Human Neuroimaging,
UCL Queen Square Institute of Neurology, University College London, London, UK
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Hara S, Hori M, Hagiwara A, Tsurushima Y, Tanaka Y, Maehara T, Aoki S, Nariai T. Myelin and Axonal Damage in Normal-Appearing White Matter in Patients with Moyamoya Disease. AJNR Am J Neuroradiol 2020; 41:1618-1624. [PMID: 32855183 DOI: 10.3174/ajnr.a6708] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Accepted: 06/05/2020] [Indexed: 12/28/2022]
Abstract
BACKGROUND AND PURPOSE Although chronic ischemia is known to induce myelin and axonal damage in animal models, knowledge regarding patients with Moyamoya disease is limited. We aimed to investigate the presence of myelin and axonal damage in Moyamoya disease and their relationship with cognitive performance. MATERIALS AND METHODS Eighteen patients with Moyamoya disease (16-55 years of age) and 18 age- and sex-matched healthy controls were evaluated with myelin-sensitive MR imaging based on magnetization transfer saturation imaging and 2-shell diffusion MR imaging. The myelin volume fraction, which reflects the amount of myelin sheath; the g-ratio, which represents the ratio of the inner (axon) to the outer (axon plus myelin) diameter of the fiber; and the axon volume fraction, which reflects axonal components, were calculated and compared between the patients and controls. In the patients with Moyamoya disease, the relationship between these parameters and cognitive task-measuring performance speed was also evaluated. RESULTS Compared with the healthy controls, the patients with Moyamoya disease showed a significant decrease in the myelin and axon volume fractions (P < .05) in many WM regions, while the increases in the g-ratio values were not statistically significant. Correlations with cognitive performance were most frequently observed with the axon volume fraction (r = 0.52-0.54; P < .03 in the right middle and posterior cerebral artery areas) and were the strongest with the g-ratio values in the right posterior cerebral artery region (r = 0.64; P = .004). CONCLUSIONS Myelin-sensitive MR imaging and diffusion MR imaging revealed that myelin and axonal damage exist in patients with Moyamoya disease. The relationship with cognitive performance might be stronger with axonal damage than with myelin damage.
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Affiliation(s)
- S Hara
- From the Department of Neurosurgery (S.H., Y.T., T.M., T.N.), Tokyo Medical and Dental University, Tokyo, Japan .,Department of Radiology (S.H., M.H., A.H., Y.T., S.A.), Juntendo University, Tokyo, Japan
| | - M Hori
- Department of Radiology (S.H., M.H., A.H., Y.T., S.A.), Juntendo University, Tokyo, Japan.,Department of Diagnostic Radiology (M.H.), Toho University Omori Medical Center, Tokyo, Japan
| | - A Hagiwara
- Department of Radiology (S.H., M.H., A.H., Y.T., S.A.), Juntendo University, Tokyo, Japan
| | - Y Tsurushima
- Department of Radiology (S.H., M.H., A.H., Y.T., S.A.), Juntendo University, Tokyo, Japan.,Department of Radiology (Y.T.), Kenshinkai Tokyo Medical Clinic, Tokyo, Japan
| | - Y Tanaka
- From the Department of Neurosurgery (S.H., Y.T., T.M., T.N.), Tokyo Medical and Dental University, Tokyo, Japan
| | - T Maehara
- From the Department of Neurosurgery (S.H., Y.T., T.M., T.N.), Tokyo Medical and Dental University, Tokyo, Japan
| | - S Aoki
- Department of Radiology (S.H., M.H., A.H., Y.T., S.A.), Juntendo University, Tokyo, Japan
| | - T Nariai
- From the Department of Neurosurgery (S.H., Y.T., T.M., T.N.), Tokyo Medical and Dental University, Tokyo, Japan
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Thapaliya K, Vegh V, Bollmann S, Barth M. Influence of 7T GRE-MRI Signal Compartment Model Choice on Tissue Parameters. Front Neurosci 2020; 14:271. [PMID: 32457565 PMCID: PMC7206227 DOI: 10.3389/fnins.2020.00271] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Accepted: 03/10/2020] [Indexed: 12/16/2022] Open
Abstract
Quantitative assessment of tissue microstructure is important in studying human brain diseases and disorders. Ultra-high field magnetic resonance imaging (MRI) data obtained using a multi-echo gradient echo sequence have been shown to contain information on myelin, axonal, and extracellular compartments in tissue. Quantitative assessment of water fraction, relaxation time (T2*), and frequency shift using multi-compartment models has been shown to be useful in studying white matter properties via specific tissue parameters. It remains unclear how tissue parameters vary with model selection based on 7T multiple echo time gradient-recalled echo (GRE) MRI data. We applied existing signal compartment models to the corpus callosum and investigated whether a three-compartment model can be reduced to two compartments and still resolve white matter parameters [i.e., myelin water fraction (MWF) and g-ratio]. We show that MWF should be computed using a three-compartment model in the corpus callosum, and the g-ratios obtained using three compartment models are consistent with previous reports. We provide results for other parameters, such as signal compartment frequency shifts.
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Affiliation(s)
- Kiran Thapaliya
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Viktor Vegh
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia.,ARC Centre for Innovation in Biomedical Imaging Technology, Brisbane, QLD, Australia
| | - Steffen Bollmann
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia.,ARC Centre for Innovation in Biomedical Imaging Technology, Brisbane, QLD, Australia
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia.,ARC Centre for Innovation in Biomedical Imaging Technology, Brisbane, QLD, Australia.,School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, Australia
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30
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Freund P, Seif M, Weiskopf N, Friston K, Fehlings MG, Thompson AJ, Curt A. MRI in traumatic spinal cord injury: from clinical assessment to neuroimaging biomarkers. Lancet Neurol 2019; 18:1123-1135. [DOI: 10.1016/s1474-4422(19)30138-3] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 03/22/2019] [Accepted: 03/28/2019] [Indexed: 01/18/2023]
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31
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David G, Mohammadi S, Martin AR, Cohen-Adad J, Weiskopf N, Thompson A, Freund P. Traumatic and nontraumatic spinal cord injury: pathological insights from neuroimaging. Nat Rev Neurol 2019; 15:718-731. [PMID: 31673093 DOI: 10.1038/s41582-019-0270-5] [Citation(s) in RCA: 100] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/18/2019] [Indexed: 01/23/2023]
Abstract
Pathophysiological changes in the spinal cord white and grey matter resulting from injury can be observed with MRI techniques. These techniques provide sensitive markers of macrostructural and microstructural tissue integrity, which correlate with histological findings. Spinal cord MRI findings in traumatic spinal cord injury (tSCI) and nontraumatic spinal cord injury - the most common form of which is degenerative cervical myelopathy (DCM) - have provided important insights into the pathophysiological processes taking place not just at the focal injury site but also rostral and caudal to the spinal injury. Although tSCI and DCM have different aetiologies, they show similar degrees of spinal cord pathology remote from the injury site, suggesting the involvement of similar secondary degenerative mechanisms. Advanced quantitative MRI protocols that are sensitive to spinal cord pathology have the potential to improve diagnosis and, more importantly, predict outcomes in patients with tSCI or nontraumatic spinal cord injury. This Review describes the insights into tSCI and DCM that have been revealed by neuroimaging and outlines current activities and future directions for the field.
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Affiliation(s)
- Gergely David
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Siawoosh Mohammadi
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, UK
| | - Allan R Martin
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
| | - Nikolaus Weiskopf
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, UK.,Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Alan Thompson
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK
| | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University Hospital Zurich, University of Zurich, Zurich, Switzerland. .,Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, London, UK. .,Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. .,Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK. .,Department of Neurology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
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32
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Schmidt H, Knösche TR. Action potential propagation and synchronisation in myelinated axons. PLoS Comput Biol 2019; 15:e1007004. [PMID: 31622338 PMCID: PMC6818808 DOI: 10.1371/journal.pcbi.1007004] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 10/29/2019] [Accepted: 09/27/2019] [Indexed: 01/11/2023] Open
Abstract
With the advent of advanced MRI techniques it has become possible to study axonal white matter non-invasively and in great detail. Measuring the various parameters of the long-range connections of the brain opens up the possibility to build and refine detailed models of large-scale neuronal activity. One particular challenge is to find a mathematical description of action potential propagation that is sufficiently simple, yet still biologically plausible to model signal transmission across entire axonal fibre bundles. We develop a mathematical framework in which we replace the Hodgkin-Huxley dynamics by a spike-diffuse-spike model with passive sub-threshold dynamics and explicit, threshold-activated ion channel currents. This allows us to study in detail the influence of the various model parameters on the action potential velocity and on the entrainment of action potentials between ephaptically coupled fibres without having to recur to numerical simulations. Specifically, we recover known results regarding the influence of axon diameter, node of Ranvier length and internode length on the velocity of action potentials. Additionally, we find that the velocity depends more strongly on the thickness of the myelin sheath than was suggested by previous theoretical studies. We further explain the slowing down and synchronisation of action potentials in ephaptically coupled fibres by their dynamic interaction. In summary, this study presents a solution to incorporate detailed axonal parameters into a whole-brain modelling framework. With more and more data becoming available on white-matter tracts, the need arises to develop modelling frameworks that incorporate these data at the whole-brain level. This requires the development of efficient mathematical schemes to study parameter dependencies that can then be matched with data, in particular the speed of action potentials that cause delays between brain regions. Here, we develop a method that describes the formation of action potentials by threshold activated currents, often referred to as spike-diffuse-spike modelling. A particular focus of our study is the dependence of the speed of action potentials on structural parameters. We find that the diameter of axons and the thickness of the myelin sheath have a strong influence on the speed, whereas the length of myelinated segments and node of Ranvier length have a lesser effect. In addition to examining single axons, we demonstrate that action potentials between nearby axons can synchronise and slow down their propagation speed.
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Affiliation(s)
- Helmut Schmidt
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- * E-mail:
| | - Thomas R. Knösche
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Biomedical Engineering and Informatics, Ilmenau University of Technology, Ilmenau, Germany
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33
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MR g-ratio-weighted connectome analysis in patients with multiple sclerosis. Sci Rep 2019; 9:13522. [PMID: 31534143 PMCID: PMC6751178 DOI: 10.1038/s41598-019-50025-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Accepted: 09/05/2019] [Indexed: 12/16/2022] Open
Abstract
Multiple sclerosis (MS) is a brain network disconnection syndrome. Although the brain network topology in MS has been evaluated using diffusion MRI tractography, the mechanism underlying disconnection in the disorder remains unclear. In this study, we evaluated the brain network topology in MS using connectomes with connectivity strengths based on the ratio of the inner to outer myelinated axon diameter (i.e., g-ratio), thereby providing enhanced sensitivity to demyelination compared with the conventional measures of connectivity. We mapped g-ratio-based connectomes in 14 patients with MS and compared them with those of 14 age- and sex-matched healthy controls. For comparison, probabilistic tractography was also used to map connectomes based on the number of streamlines (NOS). We found that g-ratio- and NOS-based connectomes comprised significant connectivity reductions in patients with MS, predominantly in the motor, somatosensory, visual, and limbic regions. However, only the g-ratio-based connectome enabled detection of significant increases in nodal strength in patients with MS. Finally, we found that the g-ratio-weighted nodal strength in motor, visual, and limbic regions significantly correlated with inter-individual variation in measures of disease severity. The g-ratio-based connectome can serve as a sensitive biomarker for diagnosing and monitoring disease progression.
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Trampel R, Bazin PL, Pine K, Weiskopf N. In-vivo magnetic resonance imaging (MRI) of laminae in the human cortex. Neuroimage 2019; 197:707-715. [DOI: 10.1016/j.neuroimage.2017.09.037] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2017] [Revised: 09/13/2017] [Accepted: 09/19/2017] [Indexed: 11/16/2022] Open
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35
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Tabelow K, Balteau E, Ashburner J, Callaghan MF, Draganski B, Helms G, Kherif F, Leutritz T, Lutti A, Phillips C, Reimer E, Ruthotto L, Seif M, Weiskopf N, Ziegler G, Mohammadi S. hMRI - A toolbox for quantitative MRI in neuroscience and clinical research. Neuroimage 2019; 194:191-210. [PMID: 30677501 PMCID: PMC6547054 DOI: 10.1016/j.neuroimage.2019.01.029] [Citation(s) in RCA: 125] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Revised: 12/21/2018] [Accepted: 01/10/2019] [Indexed: 12/20/2022] Open
Abstract
Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.
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Affiliation(s)
| | | | | | | | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Switzerland; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Gunther Helms
- Medical Radiation Physics, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Switzerland
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Switzerland
| | | | - Enrico Reimer
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | | | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Gabriel Ziegler
- Institute for Cognitive Neurology and Dementia Research, University of Magdeburg, Germany
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36
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Slater DA, Melie‐Garcia L, Preisig M, Kherif F, Lutti A, Draganski B. Evolution of white matter tract microstructure across the life span. Hum Brain Mapp 2019; 40:2252-2268. [PMID: 30673158 PMCID: PMC6865588 DOI: 10.1002/hbm.24522] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 12/28/2018] [Accepted: 01/02/2019] [Indexed: 01/13/2023] Open
Abstract
The human brain undergoes dramatic structural change over the life span. In a large imaging cohort of 801 individuals aged 7-84 years, we applied quantitative relaxometry and diffusion microstructure imaging in combination with diffusion tractography to investigate tissue property dynamics across the human life span. Significant nonlinear aging effects were consistently observed across tracts and tissue measures. The age at which white matter (WM) fascicles attain peak maturation varies substantially across tissue measurements and tracts. These observations of heterochronicity and spatial heterogeneity of tract maturation highlight the importance of using multiple tissue measurements to investigate each region of the WM. Our data further provide additional quantitative evidence in support of the last-in-first-out retrogenesis hypothesis of aging, demonstrating a strong correlational relationship between peak maturational timing and the extent of quadratic measurement differences across the life span for the most myelin sensitive measures. These findings present an important baseline from which to assess divergence from normative aging trends in developmental and degenerative disorders, and to further investigate the mechanisms connecting WM microstructure to cognition.
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Affiliation(s)
- David A. Slater
- Laboratory of Research in Neuroimaging (LREN) – Department of Clinical Neurosciences – CHUVUniversity of LausanneLausanneSwitzerland
| | - Lester Melie‐Garcia
- Laboratory of Research in Neuroimaging (LREN) – Department of Clinical Neurosciences – CHUVUniversity of LausanneLausanneSwitzerland
| | - Martin Preisig
- Department of Psychiatry – CHUVUniversity of LausanneLausanneSwitzerland
| | - Ferath Kherif
- Laboratory of Research in Neuroimaging (LREN) – Department of Clinical Neurosciences – CHUVUniversity of LausanneLausanneSwitzerland
| | - Antoine Lutti
- Laboratory of Research in Neuroimaging (LREN) – Department of Clinical Neurosciences – CHUVUniversity of LausanneLausanneSwitzerland
| | - Bogdan Draganski
- Laboratory of Research in Neuroimaging (LREN) – Department of Clinical Neurosciences – CHUVUniversity of LausanneLausanneSwitzerland
- Department of Clinical NeurosciencesMax‐Planck‐Institute for Human Cognitive and Brain SciencesLeipzigGermany
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37
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Takemura H, Ogawa S, Mezer AA, Horiguchi H, Miyazaki A, Matsumoto K, Shikishima K, Nakano T, Masuda Y. Diffusivity and quantitative T1 profile of human visual white matter tracts after retinal ganglion cell damage. NEUROIMAGE-CLINICAL 2019; 23:101826. [PMID: 31026624 PMCID: PMC6482365 DOI: 10.1016/j.nicl.2019.101826] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 03/27/2019] [Accepted: 04/13/2019] [Indexed: 02/04/2023]
Abstract
In patients with retinal ganglion cell diseases, recent diffusion tensor imaging (DTI) studies have revealed structural abnormalities in visual white matter tracts such as the optic tract, and optic radiation. However, the microstructural origin of these diffusivity changes is unknown as DTI metrics involve multiple biological factors and do not correlate directly with specific microstructural properties. In contrast, recent quantitative T1 (qT1) mapping methods provide tissue property measurements relatively specific to myelin volume fractions in white matter. This study aims to improve our understanding of microstructural changes in visual white matter tracts following retinal ganglion cell damage in Leber's hereditary optic neuropathy (LHON) patients by combining DTI and qT1 measurements. We collected these measurements from seven LHON patients and twenty age-matched control subjects. For all individuals, we identified the optic tract and the optic radiation using probabilistic tractography, and evaluated diffusivity and qT1 profiles along them. Both diffusivity and qT1 measurements in the optic tract differed significantly between LHON patients and controls. In the optic radiation, these changes were observed in diffusivity but were not evident in qT1 measurements. This suggests that myelin loss may not explain trans-synaptic diffusivity changes in the optic radiation as a consequence of retinal ganglion cell disease. Retinal ganglion cell damage affects diffusivity and T1 along visual pathways. DTI metric identified white matter change in both optic tract and optic radiation. T1 measurement in optic radiation did not exhibit abnormality, unlike DTI metric. Myelin loss may not be a major cause of diffusivity change along optic radiation.
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Affiliation(s)
- Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, and Osaka University, Suita, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita, Japan.
| | - Shumpei Ogawa
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan; Department of Ophthalmology, Atsugi city hospital, Atsugi, Japan.
| | - Aviv A Mezer
- The Edmond and Lily Safra Center for Brain Science, The Hebrew University of Jerusalem, Israel
| | - Hiroshi Horiguchi
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | | | - Kenji Matsumoto
- Brain Science Institute, Tamagawa University, Machida, Japan
| | - Keigo Shikishima
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | - Tadashi Nakano
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | - Yoichiro Masuda
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
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38
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Berman S, Filo S, Mezer AA. Modeling conduction delays in the corpus callosum using MRI-measured g-ratio. Neuroimage 2019; 195:128-139. [PMID: 30910729 DOI: 10.1016/j.neuroimage.2019.03.025] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 03/12/2019] [Accepted: 03/12/2019] [Indexed: 11/26/2022] Open
Abstract
Conduction of action potentials along myelinated axons is affected by their structural features, such as the axonal g-ratio, the ratio between the inner and outer diameters of the myelin sheath surrounding the axon. The effect of g-ratio variance on conduction properties has been quantitatively evaluated using single-axon models. It has recently become possible to estimate a g-ratio weighted measurement in vivo using quantitative MRI. Nevertheless, it is still unclear whether the variance in the g-ratio in the healthy human brain leads to significant differences in conduction velocity. In this work we tested whether the g-ratio MRI measurement can be used to predict conduction delays in the corpus callosum. We present a comprehensive framework in which the structural properties of fibers (i.e. length and g-ratio, measured using MRI), are incorporated in a biophysical model of axon conduction, to model conduction delays of long-range white matter fibers. We applied this framework to the corpus callosum, and found conduction delay estimates that are compatible with previously estimated values of conduction delays. We account for the variance in the velocity given the axon diameter distribution in the splenium, mid-body and genu, to further compare the fibers within the corpus callosum. Conduction delays have been suggested to increase with age. Therefore, we investigated whether there are differences in the g-ratio and the fiber length between young and old adults, and whether this leads to a difference in conduction speed and delays. We found very small differences between the predicted delays of the two groups in the motor fibers of the corpus callosum. We also found that the motor fibers of the corpus callosum have the fastest conduction estimates. Using the axon diameter distributions, we found that the occipital fibers have the slowest estimations, while the frontal and motor fiber tracts have similar estimates. Our study provides a framework for predicting conduction latencies in vivo. The framework could have major implications for future studies of white matter diseases and large range network computations. Our results highlight the need for improving additional in vivo measurements of white matter microstructure.
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Affiliation(s)
- S Berman
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - S Filo
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - A A Mezer
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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39
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Phillips KA, Watson CM, Bearman A, Knippenberg AR, Adams J, Ross C, Tardif SD. Age-related changes in myelin of axons of the corpus callosum and cognitive decline in common marmosets. Am J Primatol 2019; 81:e22949. [PMID: 30620098 DOI: 10.1002/ajp.22949] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 12/05/2018] [Accepted: 12/08/2018] [Indexed: 12/14/2022]
Abstract
Executive control is a higher-level cognitive function that involves a range of different processes that are involved in the planning, coordination, execution, and inhibition of responses. Many of the processes associated with executive control, such as response inhibition and mental flexibility, decline with age. Degeneration of white matter architecture is considered to be the one of the key factors underlying cognitive decline associated with aging. Here we investigated how white matter changes of the corpus callosum were related to cognitive aging in common marmosets (Callithrix jacchus). We hypothesized that reduction in myelin thickness, myelin density, and myelin fraction of axonal fibers in the corpus callosum would be associated with performance on a task of executive function in a small sample of geriatric marmosets (n = 4) and young adult marmosets (n = 2). Our results indicated declines in myelin thickness, density, and myelin fraction with age. Considerable variability was detected on these characteristics of myelin and cognitive performance assessed via the detoured reach task. Age-related changes in myelin in Region II of the corpus callosum were predictive of cognitive performance on the detoured reach task. Thus the detoured reach task appears to also measure aspects of corticostriatal function in addition to prefrontal cortical function.
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Affiliation(s)
- Kimberley A Phillips
- Department of Psychology, Trinity University, San Antonio, Texas.,Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas
| | - Chase M Watson
- Department of Psychology, Trinity University, San Antonio, Texas
| | - Ari Bearman
- Department of Psychology, Trinity University, San Antonio, Texas
| | | | - Jessica Adams
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas
| | - Corinna Ross
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas.,Department of Science and Mathematics, Texas A&M University-San Antonio, San Antonio, Texas.,Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, Texas
| | - Suzette D Tardif
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas.,Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, Texas
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40
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Lebel C, Deoni S. The development of brain white matter microstructure. Neuroimage 2018; 182:207-218. [PMID: 29305910 PMCID: PMC6030512 DOI: 10.1016/j.neuroimage.2017.12.097] [Citation(s) in RCA: 276] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 12/16/2017] [Accepted: 12/30/2017] [Indexed: 12/13/2022] Open
Abstract
Throughout infancy, childhood, and adolescence, our brains undergo remarkable changes. Processes including myelination and synaptogenesis occur rapidly across the first 2-3 years of life, and ongoing brain remodeling continues into young adulthood. Studies have sought to characterize the patterns of structural brain development, and early studies predominately relied upon gross anatomical measures of brain structure, morphology, and organization. MRI offers the ability to characterize and quantify a range of microstructural aspects of brain tissue that may be more closely related to fundamental neurodevelopmental processes. Techniques such as diffusion, magnetization transfer, relaxometry, and myelin water imaging provide insight into changing cyto- and myeloarchitecture, neuronal density, and structural connectivity. In this review, we focus on the growing body of literature exploiting these MRI techniques to better understand the microstructural changes that occur in brain white matter during maturation. Our review focuses on studies of normative brain development from birth to early adulthood (∼25 years), and places particular emphasis on longitudinal studies and newer techniques that are being used to study microstructural white matter development. All imaging methods demonstrate consistent, rapid microstructural white matter development over the first 3 years of life, suggesting increased myelination and axonal packing. Diffusion studies clearly demonstrate continued white matter maturation during later childhood and adolescence, though the lack of consistent findings in other modalities suggests changes may be mainly due to axonal packing. An emerging literature details differential microstructural development in boys and girls, and connects developmental trajectories to cognitive abilities, behaviour, and/or environmental factors, though the nature of these relationships remains unclear. Future research will need to focus on newer imaging techniques and longitudinal studies to provide more detailed information about microstructural white matter development, particularly in the childhood years.
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Affiliation(s)
- Catherine Lebel
- Department of Radiology, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute and the Hotchkiss Brain Institute, Calgary, AB, Canada.
| | - Sean Deoni
- School of Engineering, Providence, RI, United States; Advanced Baby Imaging Lab at Memorial Hospital of Rhode Island, Pawtucket, RI, United States
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41
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Morawski M, Kirilina E, Scherf N, Jäger C, Reimann K, Trampel R, Gavriilidis F, Geyer S, Biedermann B, Arendt T, Weiskopf N. Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology. Neuroimage 2018; 182:417-428. [PMID: 29196268 PMCID: PMC6189522 DOI: 10.1016/j.neuroimage.2017.11.060] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 11/22/2017] [Accepted: 11/26/2017] [Indexed: 01/21/2023] Open
Abstract
Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates.
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Affiliation(s)
- Markus Morawski
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, 04103, Leipzig, Germany.
| | - Evgeniya Kirilina
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany; Center for Cognitive Neuroscience Berlin, Free University Berlin, Habelschwerdter Allee 45, 14195, Berlin, Germany.
| | - Nico Scherf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Carsten Jäger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Katja Reimann
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, 04103, Leipzig, Germany
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Filippos Gavriilidis
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Stefan Geyer
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Bernd Biedermann
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, 04103, Leipzig, Germany
| | - Thomas Arendt
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, 04103, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
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42
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Sokolov AA, Zeidman P, Erb M, Ryvlin P, Pavlova MA, Friston KJ. Linking structural and effective brain connectivity: structurally informed Parametric Empirical Bayes (si-PEB). Brain Struct Funct 2018; 224:205-217. [PMID: 30302538 PMCID: PMC6373362 DOI: 10.1007/s00429-018-1760-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Accepted: 09/21/2018] [Indexed: 12/13/2022]
Abstract
Despite the potential for better understanding functional neuroanatomy, the complex relationship between neuroimaging measures of brain structure and function has confounded integrative, multimodal analyses of brain connectivity. This is particularly true for task-related effective connectivity, which describes the causal influences between neuronal populations. Here, we assess whether measures of structural connectivity may usefully inform estimates of effective connectivity in larger scale brain networks. To this end, we introduce an integrative approach, capitalising on two recent statistical advances: Parametric Empirical Bayes, which provides group-level estimates of effective connectivity, and Bayesian model reduction, which enables rapid comparison of competing models. Crucially, we show that structural priors derived from high angular resolution diffusion imaging on a dynamic causal model of a 12-region network-based on functional MRI data from the same subjects-substantially improve model evidence (posterior probability 1.00). This provides definitive evidence that structural and effective connectivity depend upon each other in mediating distributed, large-scale interactions in the brain. Furthermore, this work offers novel perspectives for understanding normal brain architecture and its disintegration in clinical conditions.
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Affiliation(s)
- Arseny A Sokolov
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK. .,Service de Neurologie, Département des Neurosciences Cliniques, Centre Hospitalier Universitaire Vaudois (CHUV), 1011, Lausanne, Switzerland.
| | - Peter Zeidman
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK
| | - Michael Erb
- Department of Biomedical Magnetic Resonance, Department of Radiology, University of Tübingen Medical School, 72076, Tübingen, Germany
| | - Philippe Ryvlin
- Service de Neurologie, Département des Neurosciences Cliniques, Centre Hospitalier Universitaire Vaudois (CHUV), 1011, Lausanne, Switzerland
| | - Marina A Pavlova
- Department of Psychiatry and Psychotherapy, University of Tübingen Medical School, 72076, Tübingen, Germany
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK
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43
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Calamuneri A, Arrigo A, Mormina E, Milardi D, Cacciola A, Chillemi G, Marino S, Gaeta M, Quartarone A. White Matter Tissue Quantification at Low b-Values Within Constrained Spherical Deconvolution Framework. Front Neurol 2018; 9:716. [PMID: 30210438 PMCID: PMC6122130 DOI: 10.3389/fneur.2018.00716] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 08/08/2018] [Indexed: 12/13/2022] Open
Abstract
In the last decades, a number of Diffusion Weighted Imaging (DWI) based techniques have been developed to study non-invasively human brain tissues, especially white matter (WM). In this context, Constrained Spherical Deconvolution (CSD) is recognized as being able to accurately characterize water molecules displacement, as they emerge from the observation of MR diffusion weighted (MR-DW) images. CSD is suggested to be applied on MR-DW datasets consisting of b-values around 3,000 s/mm2 and at least 45 unique diffusion weighting directions. Below such technical requirements, Diffusion Tensor Imaging (DT) remains the most widely accepted model. Unlike CSD, DTI is unable to resolve complex fiber geometries within the brain, thus affecting related tissues quantification. In addition, thanks to CSD, an index called Apparent Fiber Density (AFD) can be measured to estimate intra-axonal volume fraction within WM. In standard clinical settings, diffusion based acquisitions are well below such technical requirements. Therefore, in this study we wanted to extensively compare CSD and DTI model outcomes on really low demanding MR-DW datasets, i.e., consisting of a single shell (b-value = 1,000 s/mm2) and only 30 unique diffusion encoding directions. To this end, we performed deterministic and probabilistic tractographic reconstruction of two major WM pathways, namely the Corticospinal Tract and the Arcuate Fasciculus. We estimated and analyzed tensor based features as well as, for the first time, AFD interpretability in our data. By performing multivariate statistics and tract-based ROI analysis, we demonstrate that WM quantification is affected by both the diffusion model and threshold applied to noisy tractographic maps. Consistently with existing literature, we showed that CSD outperforms DTI even in our scenario. Most importantly, for the first time we address the problem of accuracy and interpretation of AFD in a low-demanding DW setup, and show that it is still a biological meaningful measure for the analysis of intra-axonal volume even in clinical settings.
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Affiliation(s)
| | - Alessandro Arrigo
- Department of Ophthalmology, IRCCS Ospedale San Raffaele, University Vita-Salute San Raffaele, Milan, Italy
| | - Enricomaria Mormina
- Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy.,Department of Biomedical Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Demetrio Milardi
- IRCCS Centro Neurolesi Bonino Pulejo, Messina, Italy.,Department of Biomedical Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Alberto Cacciola
- IRCCS Centro Neurolesi Bonino Pulejo, Messina, Italy.,Department of Biomedical Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | | | - Silvia Marino
- IRCCS Centro Neurolesi Bonino Pulejo, Messina, Italy
| | - Michele Gaeta
- Department of Biomedical Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Angelo Quartarone
- IRCCS Centro Neurolesi Bonino Pulejo, Messina, Italy.,Department of Biomedical Sciences and Morphological and Functional Images, University of Messina, Messina, Italy.,Fresco Institute for Parkinson's & Movement Disorders, NYU-Langone School of Medicine, New York, NY, United States
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44
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Hagiwara A, Hori M, Kamagata K, Warntjes M, Matsuyoshi D, Nakazawa M, Ueda R, Andica C, Koshino S, Maekawa T, Irie R, Takamura T, Kumamaru KK, Abe O, Aoki S. Myelin Measurement: Comparison Between Simultaneous Tissue Relaxometry, Magnetization Transfer Saturation Index, and T 1w/T 2w Ratio Methods. Sci Rep 2018; 8:10554. [PMID: 30002497 PMCID: PMC6043493 DOI: 10.1038/s41598-018-28852-6] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 07/02/2018] [Indexed: 01/06/2023] Open
Abstract
Magnetization transfer (MT) imaging has been widely used for estimating myelin content in the brain. Recently, two other approaches, namely simultaneous tissue relaxometry of R1 and R2 relaxation rates and proton density (SyMRI) and the ratio of T1-weighted to T2-weighted images (T1w/T2w ratio), were also proposed as methods for measuring myelin. SyMRI and MT imaging have been reported to correlate well with actual myelin by histology. However, for T1w/T2w ratio, such evidence is limited. In 20 healthy adults, we examined the correlation between these three methods, using MT saturation index (MTsat) for MT imaging. After calibration, white matter (WM) to gray matter (GM) contrast was the highest for SyMRI among these three metrics. Even though SyMRI and MTsat showed strong correlation in the WM (r = 0.72), only weak correlation was found between T1w/T2w and SyMRI (r = 0.45) or MTsat (r = 0.38) (correlation coefficients significantly different from each other, with p values < 0.001). In subcortical and cortical GM, these measurements showed moderate to strong correlations to each other (r = 0.54 to 0.78). In conclusion, the high correlation between SyMRI and MTsat indicates that both methods are similarly suited to measure myelin in the WM, whereas T1w/T2w ratio may be less optimal.
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Affiliation(s)
- Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
| | - Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Marcel Warntjes
- SyntheticMR AB, Linköping, Sweden
- Center for Medical Imaging Science and Visualization (CMIV), Linköping, Sweden
| | - Daisuke Matsuyoshi
- Araya Inc., Tokyo, Japan
- Research Institute for Science and Engineering, Waseda University, Waseda, Japan
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Misaki Nakazawa
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Ryo Ueda
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
- Department of Radiological Sciences, Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
- Office of Radiation Technology, Keio University Hospital, Tokyo, Japan
| | - Christina Andica
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Saori Koshino
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Tomoko Maekawa
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Ryusuke Irie
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Tomohiro Takamura
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | | | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
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45
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Hori M, Hagiwara A, Fukunaga I, Ueda R, Kamiya K, Suzuki Y, Liu W, Murata K, Takamura T, Hamasaki N, Irie R, Kamagata K, Kumamaru KK, Suzuki M, Aoki S. Application of Quantitative Microstructural MR Imaging with Atlas-based Analysis for the Spinal Cord in Cervical Spondylotic Myelopathy. Sci Rep 2018; 8:5213. [PMID: 29581458 PMCID: PMC5979956 DOI: 10.1038/s41598-018-23527-8] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Accepted: 03/15/2018] [Indexed: 12/14/2022] Open
Abstract
Mapping of MR fiber g-ratio, which is the ratio of the diameter of the axon to the diameter of the neuronal fiber, is introduced in this article. We investigated the MR fiber g-ratio, the axon volume fraction (AVF) and the myelin volume fraction (MVF) to evaluate microstructural changes in the spinal cord in patients with cervical spondylotic myelopathy (CSM) in vivo, using atlas-based analysis. We used diffusion MRI data acquired with a new simultaneous multi-slice accelerated readout-segmented echo planar imaging sequence for diffusion analysis for AVF calculation and magnetization transfer saturation imaging for MVF calculation. The AVFs of fasciculus gracilis in the affected side spinal cord, fasciculus cuneatus and lateral corticospinal tracts (LSCT) in the affected and unaffected side spinal cord were significantly lower (P = 0.019, 0.001, 0019, 0.000, and 0.002, respectively) than those of normal controls. No difference was found in the MVFs. The fiber g-ratio of LSCT was significantly lower (P = 0.040) in the affected side spinal cords than in the normal controls. The pathological microstructural changes in the spinal cord in patients with CSM, presumably partial axonal degenerations with preserved myelin. This technique has the potential to be a clinical biomarker in patients with CSM in vivo.
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Affiliation(s)
- Masaaki Hori
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.,Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Issei Fukunaga
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Ryo Ueda
- Health Science, Tokyo Metropolitan University, Tokyo, Japan
| | - Kouhei Kamiya
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yuichi Suzuki
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Wei Liu
- Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China
| | | | - Tomohiro Takamura
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Nozomi Hamasaki
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Ryusuke Irie
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan.,Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | | | - Michimasa Suzuki
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
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46
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Uesaki M, Takemura H, Ashida H. Computational neuroanatomy of human stratum proprium of interparietal sulcus. Brain Struct Funct 2018; 223:489-507. [PMID: 28871500 PMCID: PMC5772143 DOI: 10.1007/s00429-017-1492-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Accepted: 08/04/2017] [Indexed: 11/19/2022]
Abstract
Recent advances in diffusion-weighted MRI (dMRI) and tractography have enabled identification of major long-range white matter tracts in the human brain. Yet, our understanding of shorter tracts, such as those within the parietal lobe, remains limited. Over a century ago, a tract connecting the superior and inferior parts of the parietal cortex was identified in a post-mortem study: stratum proprium of interparietal sulcus (SIPS; Sachs, Das hemisphärenmark des menschlichen grosshirns. Verlag von georg thieme, Leipzig, 1892). The tract has since been replicated in another fibre dissection study (Vergani et al., Cortex 56:145-156, 2014), however, it has not been fully investigated in the living human brain and its precise anatomical properties are yet to be described. We used dMRI and tractography to identify and characterise SIPS in vivo, and explored its spatial proximity to the cortical areas associated with optic-flow processing using fMRI. SIPS was identified bilaterally in all subjects, and its anatomical position and trajectory are consistent with previous post-mortem studies. Subsequent evaluation of the tractography results using the linear fascicle evaluation and virtual lesion analysis yielded strong statistical evidence for SIPS. We also found that the SIPS endpoints are adjacent to the optic-flow selective areas. In sum, we show that SIPS is a short-range tract connecting the superior and inferior parts of the parietal cortex, wrapping around the intraparietal sulcus, and that it may be a crucial anatomy underlying optic-flow processing. In vivo identification and characterisation of SIPS will facilitate further research on SIPS in relation to cortical functions, their development, and diseases that affect them.
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Affiliation(s)
- Maiko Uesaki
- Department of Psychology, Graduate School of Letters, Kyoto University, Kyoto, Japan.
- Japan Society for the Promotion of Science, Tokyo, Japan.
- Open Innovation and Collaboration Research Organization, Ritsumeikan University, Osaka, Japan.
| | - Hiromasa Takemura
- Japan Society for the Promotion of Science, Tokyo, Japan.
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, and Osaka University, Suita, Japan.
- Graduate School of Frontier Biosciences, Osaka University, Suita, Japan.
| | - Hiroshi Ashida
- Department of Psychology, Graduate School of Letters, Kyoto University, Kyoto, Japan
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West KL, Kelm ND, Carson RP, Alexander DC, Gochberg DF, Does MD. Experimental studies of g-ratio MRI in ex vivo mouse brain. Neuroimage 2017; 167:366-371. [PMID: 29208572 DOI: 10.1016/j.neuroimage.2017.11.064] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2017] [Revised: 11/26/2017] [Accepted: 11/29/2017] [Indexed: 12/13/2022] Open
Abstract
This study aimed to experimentally evaluate a previously proposed MRI method for mapping axonal g-ratio (ratio of axon diameters, measured to the inner and outer boundary of myelin). MRI and electron microscopy were used to study excised and fixed brains of control mice and three mouse models of abnormal white matter. The results showed that g-ratio measured with MRI correlated with histological measures of myelinated axon g-ratio, but with a bias that is likely due to the presence of non-myelinated axons. The results also pointed to cases where the MRI g-ratio model simplifies to be primarily a function of total myelin content.
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Affiliation(s)
- Kathryn L West
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States; Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Nathaniel D Kelm
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States; Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Robert P Carson
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Daniel C Alexander
- Center for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Daniel F Gochberg
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Mark D Does
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States; Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; Department of Electrical Engineering, Vanderbilt University, Nashville, TN, United States.
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Carey D, Caprini F, Allen M, Lutti A, Weiskopf N, Rees G, Callaghan MF, Dick F. Quantitative MRI provides markers of intra-, inter-regional, and age-related differences in young adult cortical microstructure. Neuroimage 2017; 182:429-440. [PMID: 29203455 PMCID: PMC6189523 DOI: 10.1016/j.neuroimage.2017.11.066] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Revised: 10/19/2017] [Accepted: 11/29/2017] [Indexed: 12/17/2022] Open
Abstract
Measuring the structural composition of the cortex is critical to understanding typical development, yet few investigations in humans have charted markers in vivo that are sensitive to tissue microstructural attributes. Here, we used a well-validated quantitative MR protocol to measure four parameters (R1, MT, R2*, PD*) that differ in their sensitivity to facets of the tissue microstructural environment (R1, MT: myelin, macromolecular content; R2*: myelin, paramagnetic ions, i.e., iron; PD*: free water content). Mapping these parameters across cortical regions in a young adult cohort (18–39 years, N = 93) revealed expected patterns of increased macromolecular content as well as reduced tissue water content in primary and primary adjacent cortical regions. Mapping across cortical depth within regions showed decreased expression of myelin and related processes – but increased tissue water content – when progressing from the grey/white to the grey/pial boundary, in all regions. Charting developmental change in cortical microstructure cross-sectionally, we found that parameters with sensitivity to tissue myelin (R1 & MT) showed linear increases with age across frontal and parietal cortex (change 0.5–1.0% per year). Overlap of robust age effects for both parameters emerged in left inferior frontal, right parietal and bilateral pre-central regions. Our findings afford an improved understanding of ontogeny in early adulthood and offer normative quantitative MR data for inter- and intra-cortical composition, which may be used as benchmarks in further studies. We mapped multi-parameter maps (MPMs) across and within cortical regions. We charted age effects (ages 18–39) on myelin and related processes. MPMs sensitive to myelin (R1, MT) showed elevated values in primary areas over most cortical depths. R2* map foci tended to overlap MPMs sensitive to myelin (R1, MT). R1 and MT increased with age (0.5–1.0% per year) at mid-depth in frontal and parietal cortex.
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Affiliation(s)
- Daniel Carey
- The Irish Longitudinal Study on Aging (TILDA), Trinity College Dublin, Dublin 2, Ireland; Centre for Brain and Cognitive Development (CBCD), Birkbeck College, University of London, UK.
| | - Francesco Caprini
- Centre for Brain and Cognitive Development (CBCD), Birkbeck College, University of London, UK
| | - Micah Allen
- Institute of Cognitive Neuroscience, University College London, Queen Square, London, UK; Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London, UK
| | - Antoine Lutti
- Institute of Cognitive Neuroscience, University College London, Queen Square, London, UK; Laboratoire de Recherche en Neuroimagerie - LREN, Departement des Neurosciences Cliniques, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Nikolaus Weiskopf
- Institute of Cognitive Neuroscience, University College London, Queen Square, London, UK; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Geraint Rees
- Institute of Cognitive Neuroscience, University College London, Queen Square, London, UK; Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London, UK
| | - Martina F Callaghan
- Institute of Cognitive Neuroscience, University College London, Queen Square, London, UK
| | - Frederic Dick
- Centre for Brain and Cognitive Development (CBCD), Birkbeck College, University of London, UK; Birkbeck/UCL Centre for Neuroimaging (BUCNI), 26 Bedford Way, London, UK
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Sled JG. Modelling and interpretation of magnetization transfer imaging in the brain. Neuroimage 2017; 182:128-135. [PMID: 29208570 DOI: 10.1016/j.neuroimage.2017.11.065] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Revised: 11/19/2017] [Accepted: 11/29/2017] [Indexed: 01/09/2023] Open
Abstract
Magnetization transfer contrast has yielded insight into brain tissue microstructure changes across the lifespan and in a range of disorders. This progress has been aided by the development of quantitative magnetization transfer imaging techniques able to extract intrinsic properties of the tissue that are independent of the specifics of the data acquisition. While the tissue properties extracted by these techniques do not map directly onto specific cellular structures or pathological processes, a growing body of work from animal models and histopathological correlations aids the in vivo interpretation of magnetization transfer properties of tissue. This review examines the biophysical models that have been developed to describe magnetization transfer contrast in tissue as well as the experimental evidence for the biological interpretation of magnetization transfer data in health and disease.
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Affiliation(s)
- John G Sled
- Hospital for Sick Children, Mouse Imaging Centre, Toronto, Ontario, Canada; Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
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Thapaliya K, Vegh V, Bollmann S, Barth M. Assessment of microstructural signal compartments across the corpus callosum using multi-echo gradient recalled echo at 7 T. Neuroimage 2017; 182:407-416. [PMID: 29183776 DOI: 10.1016/j.neuroimage.2017.11.029] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Revised: 11/06/2017] [Accepted: 11/15/2017] [Indexed: 12/18/2022] Open
Abstract
Quantitative assessment of tissue microstructure is important in studying human brain diseases and disorders in which white matter is implicated, as it has been linked to demyelination, re-myelination, and axonal damage in clinical conditions. Ultra-high field magnetic resonance imaging data obtained using a multi-echo gradient echo sequence has been shown to contain information on myelin, axonal and extracellular compartments in white matter. In this study, we aimed to assess the sensitivity of a three-compartment model to estimate the variation of corresponding compartment parameters (water fraction, relaxation time and frequency shift) of the corpus callosum sub-regions, which are known to have different tissue structure. Additionally, we computed the g-ratio using myelin and axonal water fractions and performed a voxel-by-voxel analysis in the corpus callosum. Based on data acquired for ten participants, we show that the myelin compartment water fraction and T2∗ is consistent across the corpus callosum sub-regions, whilst myelin frequency shift varies. The results show that the variation in water fraction, T2∗ and frequency shift for the myelin signal compartment across the corpus callosum is smaller than for the axonal and extracellular signal compartments. The computed g-ratio was comparable to previously published studies in the corpus callosum. Our study suggests that a multi-echo GRE approach in vivo combined with a complex three-compartment model is sensitive to microstructural parameter variations across the human corpus callosum.
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Affiliation(s)
- Kiran Thapaliya
- Centre for Advanced Imaging, The University of Queensland, Queensland, Australia
| | - Viktor Vegh
- Centre for Advanced Imaging, The University of Queensland, Queensland, Australia
| | - Steffen Bollmann
- Centre for Advanced Imaging, The University of Queensland, Queensland, Australia
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, Queensland, Australia.
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