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Lee JH, Kim JY, Ryu K, Al-Masni MA, Kim TH, Han D, Kim HG, Kim DH. JUST-Net: Jointly unrolled cross-domain optimization based spatio-temporal reconstruction network for accelerated 3D myelin water imaging. Magn Reson Med 2024; 91:2483-2497. [PMID: 38342983 DOI: 10.1002/mrm.30021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/08/2024] [Accepted: 01/08/2024] [Indexed: 02/13/2024]
Abstract
PURPOSE We introduced a novel reconstruction network, jointly unrolled cross-domain optimization-based spatio-temporal reconstruction network (JUST-Net), aimed at accelerating 3D multi-echo gradient-echo (mGRE) data acquisition and improving the quality of resulting myelin water imaging (MWI) maps. METHOD An unrolled cross-domain spatio-temporal reconstruction network was designed. The main idea is to combine frequency and spatio-temporal image feature representations and to sequentially implement convolution layers in both domains. The k-space subnetwork utilizes shared information from adjacent frames, whereas the image subnetwork applies separate convolutions in both spatial and temporal dimensions. The proposed reconstruction network was evaluated for both retrospectively and prospectively accelerated acquisition. Furthermore, it was assessed in simulation studies and real-world cases with k-space corruptions to evaluate its potential for motion artifact reduction. RESULTS The proposed JUST-Net enabled highly reproducible and accelerated 3D mGRE acquisition for whole-brain MWI, reducing the acquisition time from fully sampled 15:23 to 2:22 min within a 3-min reconstruction time. The normalized root mean squared error of the reconstructed mGRE images increased by less than 4.0%, and the correlation coefficients for MWI showed a value of over 0.68 when compared to the fully sampled reference. Additionally, the proposed method demonstrated a mitigating effect on both simulated and clinical motion-corrupted cases. CONCLUSION The proposed JUST-Net has demonstrated the capability to achieve high acceleration factors for 3D mGRE-based MWI, which is expected to facilitate widespread clinical applications of MWI.
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Affiliation(s)
- Jae-Hun Lee
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
- Artificial Intelligence and Robotics Institute, Korea Institute of Science and Technology, Seoul, Republic of Korea
| | - Jae-Yoon Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Kanghyun Ryu
- Artificial Intelligence and Robotics Institute, Korea Institute of Science and Technology, Seoul, Republic of Korea
| | - Mohammed A Al-Masni
- Department of Artificial Intelligence, Sejong University, Seoul, Republic of Korea
| | - Tae Hyung Kim
- Department of Computer Engineering, Hongik University, Seoul, Republic of Korea
| | - Dongyeob Han
- Siemens Healthineers Ltd, Seoul, Republic of Korea
| | - Hyun Gi Kim
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
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Kawaguchi S, Kan H, Uchida Y, Kasai H, Hiwatashi A, Ueki Y. Anisotropy of the R1/T2* value dependent on white matter fiber orientation with respect to the B0 field. Magn Reson Imaging 2024; 109:83-90. [PMID: 38387713 DOI: 10.1016/j.mri.2024.02.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 02/19/2024] [Accepted: 02/19/2024] [Indexed: 02/24/2024]
Abstract
The R1 (1/T1) map divided by the T2* map (R1/T2* map) draws attention as a high-resolution myelin-related map. However, both R1 and R2* (1/T2*) values demonstrate anisotropy dependent on the white matter (WM) fiber orientation with respect to the static magnetic (B0) field. Therefore, this study primarily aimed to investigate the comprehensive impact of these angular-dependent anisotropies on the R1/T2* value. This study enrolled 10 healthy human volunteers (age = 25 ± 1.3) on the 3.0 T MRI system. For R1/T2* map calculation, whole brain R1 and T2* maps were repeatedly obtained in three head tilt positions by magnetization-prepared two rapid gradient echoes and multiple spoiled gradient echo sequences, respectively. Afterward, all maps were spatially normalized and registered to the Johns Hopkins University WM atlas. R1/T2*, R1, and R2* values were binned for fiber orientation related to the B0 field, which was estimated from diffusion-weighted echo-planar imaging data with 3° intervals, to investigate angular-dependent anisotropies in vivo. A larger change in the R1/T2* value in the global WM region as a function of fiber orientation with respect to the B0 field was observed compared to the R1 and R2* values alone. The minimum R1/T2* value at the near magic-angle range was 18.86% lower than the maximum value at the perpendicular angle range. Furthermore, R1/T2* values in the corpus callosum tract and the right and left cingulum cingulate gyrus tracts changed among the three head tilt positions due to fiber orientation changes. In conclusion, the R1/T2* value demonstrates distinctive and complicated angular-dependent anisotropy indicating the trends of both R1 and R2* values and may provide supplemental information for detecting slight changes in the microstructure of myelin and axons.
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Affiliation(s)
| | - Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Japan; Department of Radiology, Nagoya City University Graduate School of Medical Sciences, Japan.
| | - Yuto Uchida
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Japan
| | - Harumasa Kasai
- Department of Radiology, Nagoya City University Hospital, Japan
| | - Akio Hiwatashi
- Department of Radiology, Nagoya City University Graduate School of Medical Sciences, Japan
| | - Yoshino Ueki
- Department of Rehabilitation Medicine, Nagoya City University Graduate School of Medical Sciences, Japan
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Baadsvik EL, Weiger M, Froidevaux R, Schildknecht CM, Ineichen BV, Pruessmann KP. Myelin bilayer mapping in the human brain in vivo. Magn Reson Med 2024; 91:2332-2344. [PMID: 38171541 DOI: 10.1002/mrm.29998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 11/27/2023] [Accepted: 12/15/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE To quantitatively map the myelin lipid-protein bilayer in the live human brain. METHODS This goal was pursued by integrating a multi-TE acquisition approach targeting ultrashort T2 signals with voxel-wise fitting to a three-component signal model. Imaging was performed at 3 T in two healthy volunteers using high-performance RF and gradient hardware and the HYFI sequence. The design of a suitable imaging protocol faced substantial constraints concerning SNR, imaging volume, scan time, and RF power deposition. Model fitting to data acquired using the proposed protocol was made feasible through simulation-based optimization, and filtering was used to condition noise presentation and overall depiction fidelity. RESULTS A multi-TE protocol (11 TEs of 20-780 μs) for in vivo brain imaging was developed in adherence with applicable safety regulations and practical scan time limits. Data acquired using this protocol produced accurate model fitting results, validating the suitability of the protocol for this purpose. Structured, grainy texture of myelin bilayer maps was observed and determined to be a manifestation of correlated image noise resulting from the employed acquisition strategy. Map quality was significantly improved by filtering to uniformize the k-space noise distribution and simultaneously extending the k-space support. The final myelin bilayer maps provided selective depiction of myelin, reconciling competitive resolution (1.4 mm) with adequate SNR and benign noise texture. CONCLUSION Using the proposed technique, quantitative maps of the myelin bilayer can be obtained in vivo. These maps offer unique information content with potential applications in basic research, diagnosis, disease monitoring, and drug development.
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Affiliation(s)
- Emily Louise Baadsvik
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Markus Weiger
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Romain Froidevaux
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | | | - Benjamin Victor Ineichen
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Center for Reproducible Science, University of Zurich, Zurich, Switzerland
| | - Klaas Paul Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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Lee CH, Holloman M, Salzer JL, Zhang J. Multi-parametric MRI can detect enhanced myelination in the Gli1 -/- mouse brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.20.567957. [PMID: 38045415 PMCID: PMC10690149 DOI: 10.1101/2023.11.20.567957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
This study investigated the potential of combining multiple MR parameters to enhance the characterization of myelin in the mouse brain. We collected ex vivo multi-parametric MR data at 7 Tesla from control and Gli1 -/- mice; the latter exhibit enhanced myelination at postnatal day 10 (P10) in the corpus callosum and cortex. The MR data included relaxivity, magnetization transfer, and diffusion measurements, each targeting distinct myelin properties. This analysis was followed by and compared to myelin basic protein (MBP) staining of the same samples. Although a majority of the MR parameters included in this study showed significant differences in the corpus callosum between the control and Gli1 -/- mice, only T 2 , T 1 /T 2, and radial diffusivity (RD) demonstrated a significant correlation with MBP values. Based on data from the corpus callosum, partial least square regression suggested that combining T 2 , T 1 /T 2 , and inhomogeneous magnetization transfer ratio could explain approximately 80% of the variance in the MBP values. Myelin predictions based on these three parameters yielded stronger correlations with the MBP values in the P10 mouse brain corpus callosum than any single MR parameter. In the motor cortex, combining T 2 , T 1 /T 2, and radial kurtosis could explain over 90% of the variance in the MBP values at P10. This study demonstrates the utility of multi-parametric MRI in improving the detection of myelin changes in the mouse brain.
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Liu J, Jakary A, Villanueva-Meyer JE, Butowski NA, Saloner D, Clarke JL, Taylor JW, Oberheim Bush NA, Chang SM, Xu D, Lupo JM. Automatic Brain Tissue and Lesion Segmentation and Multi-Parametric Mapping of Contrast-Enhancing Gliomas without the Injection of Contrast Agents: A Preliminary Study. Cancers (Basel) 2024; 16:1524. [PMID: 38672606 PMCID: PMC11049314 DOI: 10.3390/cancers16081524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 04/08/2024] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
This study aimed to develop a rapid, 1 mm3 isotropic resolution, whole-brain MRI technique for automatic lesion segmentation and multi-parametric mapping without using contrast by continuously applying balanced steady-state free precession with inversion pulses throughout incomplete inversion recovery in a single 6 min scan. Modified k-means clustering was performed for automatic brain tissue and lesion segmentation using distinct signal evolutions that contained mixed T1/T2/magnetization transfer properties. Multi-compartment modeling was used to derive quantitative multi-parametric maps for tissue characterization. Fourteen patients with contrast-enhancing gliomas were scanned with this sequence prior to the injection of a contrast agent, and their segmented lesions were compared to conventionally defined manual segmentations of T2-hyperintense and contrast-enhancing lesions. Simultaneous T1, T2, and macromolecular proton fraction maps were generated and compared to conventional 2D T1 and T2 mapping and myelination water fraction mapping acquired with MAGiC. The lesion volumes defined with the new method were comparable to the manual segmentations (r = 0.70, p < 0.01; t-test p > 0.05). The T1, T2, and macromolecular proton fraction mapping values of the whole brain were comparable to the reference values and could distinguish different brain tissues and lesion types (p < 0.05), including infiltrating tumor regions within the T2-lesion. Highly efficient, whole-brain, multi-contrast imaging facilitated automatic lesion segmentation and quantitative multi-parametric mapping without contrast, highlighting its potential value in the clinic when gadolinium is contraindicated.
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Affiliation(s)
- Jing Liu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
| | - Angela Jakary
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
| | - Javier E. Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
| | - Nicholas A. Butowski
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
| | - David Saloner
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
- Radiology Service, VA Medical Center, San Francisco, CA 94121, USA
| | - Jennifer L. Clarke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Jennie W. Taylor
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Nancy Ann Oberheim Bush
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Susan M. Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA; (N.A.B.); (J.L.C.); (S.M.C.)
| | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
- UCSF/UC Berkeley Graduate Program in Bioengineering, University of California San Francisco and Berkeley, San Francisco, CA 94143, USA
| | - Janine M. Lupo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; (A.J.); (D.X.)
- UCSF/UC Berkeley Graduate Program in Bioengineering, University of California San Francisco and Berkeley, San Francisco, CA 94143, USA
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Sethi S, Friesen-Waldner LJ, Regnault TRH, McKenzie CA. Quantifying Brain Myelin Water Fraction in a Guinea Pig Model of Spontaneous Intrauterine Growth Restriction. J Magn Reson Imaging 2024. [PMID: 38445838 DOI: 10.1002/jmri.29332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 02/17/2024] [Accepted: 02/20/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND Intrauterine growth restriction (IUGR) is an obstetrical condition where a fetus has not achieved its genetic potential. A consequence of IUGR is a decrease in brain myelin content. Myelin water imaging (MWI) has been used to assess fetal myelin water fraction (MWF) and might potentially assess myelination changes associated with IUGR. PURPOSE To quantify and compare the MWF of non-IUGR and IUGR fetal guinea pigs (GPs) in late gestation. STUDY TYPE Prospective animal model. ANIMAL MODEL Dunkin-Hartley GP model of spontaneous IUGR (mean ± SD: 60 ± 1.2 days gestation; 19 IUGR, 52 control). FIELD STRENGTH/SEQUENCE Eight spoiled gradient-recalled (SPGR) gradient echo volumes (flip angles [α]: 2°-16°), and two sets of eight balanced steady-state free precession (bSSFP) gradient echo volumes (α: 8° - 64°), at 0° and 180° phase increments, at 3.0 T. ASSESSMENT MWF maps were generated for each fetal GP brain using multicomponent driven equilibrium single pulse observation of T1 /T2 (mcDESPOT). MWF was quantified in the fetal corpus callosum (CC), fornix (FOR), parasagittal white matter (PSW), and whole fetal brain. STATISTICAL TESTS Linear regression was performed between five fetal IUGR markers (body volume, body-to-pregnancy volume ratio, brain-to-liver volume ratio, brain-to-placenta volume ratio, and brain-to-body volume ratio) and MWF (coefficient of determination, R2 ). A t-test with a linear mixed model compared the MWF of non-IUGR and IUGR fetal GPs (significance was determined at α < 0.05). RESULTS The MWF of the control fetuses are (mean ± SD): 0.23 ± 0.02 (CC), 0.31 ± 0.02 (FOR), 0.28 ± 0.02 (PSW), and 0.20 ± 0.01 (whole brain). The MWF of the IUGR fetuses are (mean ± SD): 0.19 ± 0.02 (CC), 0.27 ± 0.01 (FOR), 0.24 ± 0.03 (PSW), and 0.16 ± 0.01 (whole brain). Significant differences in MWF were found between the non-IUGR and IUGR fetuses in every comparison. DATA CONCLUSION The mean MWF of IUGR fetal GPs is significantly lower than non-IUGR fetal GPs. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Simran Sethi
- Department of Medical Biophysics, Western University, London, Ontario, Canada
| | | | - Timothy R H Regnault
- Department of Obstetrics & Gynaecology, Western University, London, Ontario, Canada
- Department of Physiology & Pharmacology, Western University, London, Ontario, Canada
- Division of Maternal, Fetal and Newborn Health, Children's Health Research Institute, Lawson Health Research Institute, London, Ontario, Canada
| | - Charles A McKenzie
- Department of Medical Biophysics, Western University, London, Ontario, Canada
- Division of Maternal, Fetal and Newborn Health, Children's Health Research Institute, Lawson Health Research Institute, London, Ontario, Canada
- Robarts Research Institute, Western University, London, Ontario, Canada
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Schäper J, Bieri O. Myelin water imaging at 0.55 T using a multigradient-echo sequence. Magn Reson Med 2024; 91:1043-1056. [PMID: 38010053 DOI: 10.1002/mrm.29949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/19/2023] [Accepted: 11/12/2023] [Indexed: 11/29/2023]
Abstract
PURPOSE To investigate the prospects of a multigradient-echo (mGRE) acquisition for in vivo myelin water imaging at 0.55 T. METHODS Scans were performed on the brain of four healthy volunteers at 0.55 and 3 T, using a 3D mGRE sequence. The myelin water fraction (MWF) was calculated for both field strengths using a nonnegative least squares (NNLS) algorithm, implemented in the qMRLab suite. The quality of these maps as well as single-voxel fits were compared visually for 0.55 and 3 T. RESULTS The obtained MWF values at 0.55 T are consistent with previously reported ones at higher field strengths. The MWF maps are a considerable improvement over the ones at 3 T. Example fits show that 0.55 T data is better described by an exponential model than 3 T data, making the assumed multi-exponential model of the NNLS algorithm more accurate. CONCLUSION This first assessment shows that mGRE myelin water imaging at 0.55 T is feasible and has the potential to yield better results than at higher fields.
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Affiliation(s)
- Jessica Schäper
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Oliver Bieri
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
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Franklin RJM, Bodini B, Goldman SA. Remyelination in the Central Nervous System. Cold Spring Harb Perspect Biol 2024; 16:a041371. [PMID: 38316552 PMCID: PMC10910446 DOI: 10.1101/cshperspect.a041371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
The inability of the mammalian central nervous system (CNS) to undergo spontaneous regeneration has long been regarded as a central tenet of neurobiology. However, while this is largely true of the neuronal elements of the adult mammalian CNS, save for discrete populations of granule neurons, the same is not true of its glial elements. In particular, the loss of oligodendrocytes, which results in demyelination, triggers a spontaneous and often highly efficient regenerative response, remyelination, in which new oligodendrocytes are generated and myelin sheaths are restored to denuded axons. Yet remyelination in humans is not without limitation, and a variety of demyelinating conditions are associated with sustained and disabling myelin loss. In this work, we will (1) review the biology of remyelination, including the cells and signals involved; (2) describe when remyelination occurs and when and why it fails, including the consequences of its failure; and (3) discuss approaches for therapeutically enhancing remyelination in demyelinating diseases of both children and adults, both by stimulating endogenous oligodendrocyte progenitor cells and by transplanting these cells into demyelinated brain.
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Affiliation(s)
- Robin J M Franklin
- Altos Labs Cambridge Institute of Science, Cambridge CB21 6GH, United Kingdom
| | - Benedetta Bodini
- Sorbonne Université, Paris Brain Institute, CNRS, INSERM, Paris 75013, France
- Saint-Antoine Hospital, APHP, Paris 75012, France
| | - Steven A Goldman
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, New York 14642, USA
- University of Copenhagen Faculty of Medicine, Copenhagen 2200, Denmark
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Gangadin SS, Mandl RCW, de Witte LD, van Haren NEM, Schutte MJL, Begemann MJH, Kahn RS, Sommer IEC. Lower fractional anisotropy without evidence for neuro-inflammation in patients with early-phase schizophrenia spectrum disorders. Schizophr Res 2024; 264:557-566. [PMID: 36577563 DOI: 10.1016/j.schres.2022.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 12/05/2022] [Accepted: 12/07/2022] [Indexed: 12/28/2022]
Abstract
Various lines of research suggest immune dysregulation as a potential therapeutic target for negative and cognitive symptoms in schizophrenia spectrum disorders (SSD). Immune dysregulation would lead to higher extracellular free-water (EFW) in cerebral white matter (WM), which may partially underlie the frequently reported lower fractional anisotropy (FA) in SSD. We aim to investigate differences in EFW concentrations - a presumed proxy for neuro-inflammation - between early-phase SSD patients (n = 55) and healthy controls (HC; n = 37), and to explore immunological and cognitive correlates. To increase specificity for EFW, we study several complementary magnetic resonance imaging contrasts that are sensitive to EFW. FA, mean diffusivity (MD), magnetization transfer ratio (MTR), myelin water fraction (MWF) and quantitative T1 and T2 were calculated from diffusion-weighted imaging (DWI), magnetization transfer imaging (MTI) and multicomponent driven equilibrium single-pulse observation of T1/T2 (mcDESPOT). For each measure, WM skeletons were constructed with tract-based spatial statistics. Multivariate SSD-HC comparisons with WM skeletons and their average values (i.e. global WM) were not statistically significant. In voxel-wise analyses, FA was significantly lower in SSD in the genu of the corpus callosum and in the left superior longitudinal fasciculus (p < 0.04). Global WM measures did not correlate with immunological markers (i.e. IL1-RA, IL-6, IL-8, IL-10 and CRP) or cognition in HC and SSD after corrections for multiple comparisons. We confirmed lower FA in early-phase SSD patients. However, nonFA measures did not provide additional evidence for immune dysregulation or for higher EFW as the primary mechanism underlying the reported lower FA values in SSD.
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Affiliation(s)
- Shiral S Gangadin
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | - René C W Mandl
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Lot D de Witte
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
| | - Neeltje E M van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center-Sophia Children's Hospital, Rotterdam, the Netherlands.
| | - Maya J L Schutte
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | - Marieke J H Begemann
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | - René S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
| | - Iris E C Sommer
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
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Morrissey ZD, Gao J, Shetti A, Li W, Zhan L, Li W, Fortel I, Saido T, Saito T, Ajilore O, Cologna SM, Lazarov O, Leow AD. Temporal Alterations in White Matter in An App Knock-In Mouse Model of Alzheimer's Disease. eNeuro 2024; 11:ENEURO.0496-23.2024. [PMID: 38290851 PMCID: PMC10897532 DOI: 10.1523/eneuro.0496-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/05/2024] [Accepted: 01/17/2024] [Indexed: 02/01/2024] Open
Abstract
Alzheimer's disease (AD) is the most common form of dementia and results in neurodegeneration and cognitive impairment. White matter (WM) is affected in AD and has implications for neural circuitry and cognitive function. The trajectory of these changes across age, however, is still not well understood, especially at earlier stages in life. To address this, we used the AppNL-G-F/NL-G-F knock-in (APPKI) mouse model that harbors a single copy knock-in of the human amyloid precursor protein (APP) gene with three familial AD mutations. We performed in vivo diffusion tensor imaging (DTI) to study how the structural properties of the brain change across age in the context of AD. In late age APPKI mice, we observed reduced fractional anisotropy (FA), a proxy of WM integrity, in multiple brain regions, including the hippocampus, anterior commissure (AC), neocortex, and hypothalamus. At the cellular level, we observed greater numbers of oligodendrocytes in middle age (prior to observations in DTI) in both the AC, a major interhemispheric WM tract, and the hippocampus, which is involved in memory and heavily affected in AD, prior to observations in DTI. Proteomics analysis of the hippocampus also revealed altered expression of oligodendrocyte-related proteins with age and in APPKI mice. Together, these results help to improve our understanding of the development of AD pathology with age, and imply that middle age may be an important temporal window for potential therapeutic intervention.
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Affiliation(s)
- Zachery D Morrissey
- Graduate Program in Neuroscience, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Psychiatry, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Anatomy & Cell Biology, University of Illinois Chicago, Chicago, Illinois 60612
| | - Jin Gao
- Department of Electrical & Computer Engineering, University of Illinois Chicago, Chicago, Illinois 60607
- Preclinical Imaging Core, University of Illinois Chicago, Chicago, Illinois 60612
| | - Aashutosh Shetti
- Department of Anatomy & Cell Biology, University of Illinois Chicago, Chicago, Illinois 60612
| | - Wenping Li
- Department of Chemistry, University of Illinois Chicago, Chicago, Illinois 60607
| | - Liang Zhan
- Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
| | - Weiguo Li
- Preclinical Imaging Core, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Bioengineering, University of Illinois Chicago, Chicago, Illinois 60607
- Department of Radiology, Northwestern University, Chicago, Illinois 60611
| | - Igor Fortel
- Department of Bioengineering, University of Illinois Chicago, Chicago, Illinois 60607
| | - Takaomi Saido
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Wako 351-0198, Japan
| | - Takashi Saito
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University, Nagoya 467-8601, Japan
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois Chicago, Chicago, Illinois 60612
| | - Stephanie M Cologna
- Department of Chemistry, University of Illinois Chicago, Chicago, Illinois 60607
| | - Orly Lazarov
- Department of Anatomy & Cell Biology, University of Illinois Chicago, Chicago, Illinois 60612
| | - Alex D Leow
- Department of Psychiatry, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Bioengineering, University of Illinois Chicago, Chicago, Illinois 60607
- Department of Computer Science, University of Illinois Chicago, Chicago, Illinois 60607
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11
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Thakkar RN, Patel D, Kioutchoukova IP, Al-Bahou R, Reddy P, Foster DT, Lucke-Wold B. Leukodystrophy Imaging: Insights for Diagnostic Dilemmas. Med Sci (Basel) 2024; 12:7. [PMID: 38390857 PMCID: PMC10885080 DOI: 10.3390/medsci12010007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/09/2023] [Accepted: 12/13/2023] [Indexed: 02/24/2024] Open
Abstract
Leukodystrophies, a group of rare demyelinating disorders, mainly affect the CNS. Clinical presentation of different types of leukodystrophies can be nonspecific, and thus, imaging techniques like MRI can be used for a more definitive diagnosis. These diseases are characterized as cerebral lesions with characteristic demyelinating patterns which can be used as differentiating tools. In this review, we talk about these MRI study findings for each leukodystrophy, associated genetics, blood work that can help in differentiation, emerging diagnostics, and a follow-up imaging strategy. The leukodystrophies discussed in this paper include X-linked adrenoleukodystrophy, metachromatic leukodystrophy, Krabbe's disease, Pelizaeus-Merzbacher disease, Alexander's disease, Canavan disease, and Aicardi-Goutières Syndrome.
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Affiliation(s)
- Rajvi N. Thakkar
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Drashti Patel
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | | | - Raja Al-Bahou
- College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Pranith Reddy
- College of Medicine, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Devon T. Foster
- College of Medicine, Florida International University, Miami, FL 33199, USA
| | - Brandon Lucke-Wold
- Department of Neurosurgery, University of Florida, 1600 SW Archer Rd., Gainesville, FL 32610, USA
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12
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Weeda MM, van Nederpelt DR, Twisk JWR, Brouwer I, Kuijer JPA, van Dam M, Hulst HE, Killestein J, Barkhof F, Vrenken H, Pouwels PJW. Multimodal MRI study on the relation between WM integrity and connected GM atrophy and its effect on disability in early multiple sclerosis. J Neurol 2024; 271:355-373. [PMID: 37716917 PMCID: PMC10769935 DOI: 10.1007/s00415-023-11937-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 08/09/2023] [Accepted: 08/11/2023] [Indexed: 09/18/2023]
Abstract
BACKGROUND Multiple sclerosis (MS) is characterized by pathology in white matter (WM) and atrophy of grey matter (GM), but it remains unclear how these processes are related, or how they influence clinical progression. OBJECTIVE To study the spatial and temporal relationship between GM atrophy and damage in connected WM in relapsing-remitting (RR) MS in relation to clinical progression. METHODS Healthy control (HC) and early RRMS subjects visited our center twice with a 1-year interval for MRI and clinical examinations, including the Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Functional Composite (MSFC) scores. RRMS subjects were categorized as MSFC decliners or non-decliners based on ΔMSFC over time. Ten deep (D)GM and 62 cortical (C) GM structures were segmented and probabilistic tractography was performed to identify the connected WM. WM integrity was determined per tract with, amongst others, fractional anisotropy (FA), mean diffusivity (MD), neurite density index (NDI), and myelin water fraction (MWF). Linear mixed models (LMMs) were used to investigate GM and WM differences between HC and RRMS, and between MSFC decliners and non-decliners. LMM was also used to test associations between baseline WM z-scores and changes in connected GM z-scores, and between baseline GM z-scores and changes in connected WM z-scores, in HC/RRMS subjects and in MSFC decliners/non-decliners. RESULTS We included 13 HCs and 31 RRMS subjects with an average disease duration of 3.5 years and a median EDSS of 3.0. Fifteen RRMS subjects showed declining MSFC scores over time, and they showed higher atrophy rates and greater WM integrity loss compared to non-decliners. Lower baseline WM integrity was associated with increased CGM atrophy over time in RRMS, but not in HC subjects. This effect was only seen in MSFC decliners, especially when an extended WM z-score was used, which included FA, MD, NDI and MWF. Baseline GM measures were not significantly related to WM integrity changes over time in any of the groups. DISCUSSION Lower baseline WM integrity was related to more cortical atrophy in RRMS subjects that showed clinical progression over a 1-year follow-up, while baseline GM did not affect WM integrity changes over time. WM damage, therefore, seems to drive atrophy more than conversely.
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Affiliation(s)
- Merlin M Weeda
- MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.
| | - D R van Nederpelt
- MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - J W R Twisk
- Epidemiology and Data Science, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - I Brouwer
- MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - J P A Kuijer
- MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - M van Dam
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - H E Hulst
- Health-, Medical-, and Neuropsychology Unit, Institute of Psychology, Leiden University, Leiden, The Netherlands
| | - J Killestein
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - F Barkhof
- MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- UCL Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - H Vrenken
- MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - P J W Pouwels
- MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
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13
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Kim HG, Han D, Kim J, Choi JS, Cho KO. 3D MR fingerprinting-derived myelin water fraction characterizing brain development and leukodystrophy. J Transl Med 2023; 21:914. [PMID: 38102606 PMCID: PMC10725020 DOI: 10.1186/s12967-023-04788-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 12/06/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Magnetic resonance fingerprinting (MRF) enables fast myelin quantification via the myelin water fraction (MWF), offering a noninvasive method to assess brain development and disease. However, MRF-derived MWF lacks histological evaluation and remains unexamined in relation to leukodystrophy. This study aimed to access MRF-derived MWF through histology in mice and establish links between myelin, development, and leukodystrophy in mice and children, demonstrating its potential applicability in animal and human studies. METHODS 3D MRF was performed on normal C57BL/6 mice with different ages, megalencephalic leukoencephalopathy with subcortical cyst 1 wild type (MLC1 WT, control) mice, and MLC 1 knock-out (MLC1 KO, leukodystrophy) mice using a 3 T MRI. MWF values were analyzed from 3D MRF data, and histological myelin quantification was carried out using immunohistochemistry to anti-proteolipid protein (PLP) in the corpus callosum and cortex. The associations between 'MWF and PLP' and 'MWF and age' were evaluated in C57BL/6 mice. MWF values were compared between MLC1 WT and MLC1 KO mice. MWF of normal developing children were retrospectively collected and the association between MWF and age was assessed. RESULTS In 35 C57BL/6 mice (age range; 3 weeks-48 weeks), MWF showed positive relations with PLP immunoreactivity in the corpus callosum (β = 0.0006, P = 0.04) and cortex (β = 0.0005, P = 0.006). In 12-week-old C57BL/6 mice MWF showed positive relations with PLP immunoreactivity (β = 0.0009, P = 0.003, R2 = 0.54). MWF in the corpus callosum (β = 0.0022, P < 0.001) and cortex (β = 0.0010, P < 0.001) showed positive relations with age. Seven MLC1 WT and 9 MLC1 KO mice showed different MWF values in the corpus callous (P < 0.001) and cortex (P < 0.001). A total of 81 children (median age, 126 months; range, 0-199 months) were evaluated and their MWF values according to age showed the best fit for the third-order regression model (adjusted R2 range, 0.44-0.94, P < 0.001). CONCLUSION MWF demonstrated associations with histologic myelin quantity, age, and the presence of leukodystrophy, underscoring the potential of 3D MRF-derived MWF as a rapid and noninvasive quantitative indicator of brain myelin content in both mice and humans.
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Affiliation(s)
- Hyun Gi Kim
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | | | - Jimin Kim
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jeong-Sun Choi
- Department of Pharmacology, Department of Biomedicine & Health Sciences, Catholic Neuroscience Institute, Institute for Aging and Metabolic Diseases, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-Gu, Seoul, 06591, South Korea
| | - Kyung-Ok Cho
- Department of Pharmacology, Department of Biomedicine & Health Sciences, Catholic Neuroscience Institute, Institute for Aging and Metabolic Diseases, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-Gu, Seoul, 06591, South Korea.
- CMC Institute for Basic Medical Science, The Catholic Medical Center of The Catholic University of Korea, Seoul, Korea.
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14
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Cho H, Han S, Cho HJ. Empirical relationship between TEM-derived myelin volume fraction and MRI-R 2 values in aging ex vivo rat corpus callosum. Magn Reson Imaging 2023; 103:75-83. [PMID: 37451521 DOI: 10.1016/j.mri.2023.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/26/2023] [Accepted: 07/09/2023] [Indexed: 07/18/2023]
Abstract
Ex vivo ratiometric measurements of short- and long-T2 components using the multiple spin echo sequence of MRI are often employed to evaluate alterations in myelin content in the white matter (WM) of the brain. However, the relationship between absolute MRI-T2 values (long-T2 component) and myelin volumetric information in aged ex vivo rodent WM appears to be influenced by factors such as animal species, field strength, and fixation durations/washing. Here, multiple spin echo sequence-based MRI-R2 (the reciprocal of T2) values were measured in the corpus callosum (CC) region in the post-mortem rat brains (n = 9) of different age groups with common fixation techniques without washing at 7 T. Transmission electron microscopy (TEM)-based quantification of myelin volume fraction (MVF) and corresponding Monte-Carlo simulation to estimate relaxation rates (R2,IE) due to diffusion in the presence of inhomogeneous magnetic field perturbation in intra- and extra-cellular (IE) spaces were respectively performed. To determine whether the short-T2 components originating from myelin water were mixed with long-T2 components from IE water or were undetectable, the MVF values obtained from TEM results were respectively compared with MRI-R2 and R2,IE values. A significant correlation (Pearson's correlation coefficient r = 0.8763; p < 0.01) of average MRI-R2 and MVF values was observed. Estimated R2,IE values from Monte-Carlo simulations in IE water signals were also positively correlated (r = 0.8281; p < 0.01) with MVF values. However, the magnitudes of R2,IE values were much smaller than those observed for MRI-R2 values, indicating that changes in R2 related MVF are likely dominated by myelin water components. Such comparisons between independent parameters from MRI, TEM, and simulations support the suggestion that myelin water signals were indistinguishably mixed to exhibit mono-exponential T2 relaxation, and multiple spin echo sequence-based MRI-R2 values in aging ex vivo rat CC without prolonged washing still reflect the volumetric information of myelin, likely due to enhanced water exchange across the myelin.
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Affiliation(s)
- Hwapyeong Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Sohyun Han
- Research Equipment Operations Division, Korea Basic Science Institute, Cheongju, South Korea.
| | - Hyung Joon Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea.
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15
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Economou M, Bempt FV, Van Herck S, Wouters J, Ghesquière P, Vanderauwera J, Vandermosten M. Myelin plasticity during early literacy training in at-risk pre-readers. Cortex 2023; 167:86-100. [PMID: 37542803 DOI: 10.1016/j.cortex.2023.05.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 04/09/2023] [Accepted: 05/31/2023] [Indexed: 08/07/2023]
Abstract
A growing body of neuroimaging evidence shows that white matter can change as a result of experience and structured learning. Although the majority of previous work has used diffusion MRI to characterize such changes in white matter, diffusion metrics offer limited biological specificity about which microstructural features may be driving white matter plasticity. Recent advances in myelin-specific MRI techniques offer a promising opportunity to assess the specific contribution of myelin in learning-related plasticity. Here we describe the application of such an approach to examine structural plasticity during an early intervention in preliterate children at risk for dyslexia. To this end, myelin water imaging data were collected before and after a 12-week period in (1) at-risk children following early literacy training (n = 13-24), (2) at-risk children engaging with other non-literacy games (n = 10-17) and (3) children without a risk receiving no training (n = 11-22). Before the training, regional risk-related differences were identified, showing higher myelin water fraction (MWF) in right dorsal white matter in at-risk children compared to the typical control group. Concerning intervention-specific effects, our results revealed an increase across left-hemispheric and right ventral MWF over the course of training in the at-risk children receiving early literacy training, but not in the at-risk active control group or the no-risk typical control group. Overall, our results provide support for the use of myelin water imaging as a sensitive tool to investigate white matter and offer a first indication of myelin plasticity in young children at the onset of literacy acquisition.
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Affiliation(s)
- Maria Economou
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium; Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium
| | - Femke Vanden Bempt
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium; Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium
| | - Shauni Van Herck
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium; Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium
| | - Jan Wouters
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium
| | - Pol Ghesquière
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium
| | - Jolijn Vanderauwera
- Psychological Sciences Research Institute, Université Catholique de Louvain, 1348, Louvain-la-Neuve, Belgium; Institute of Neuroscience, Université Catholique de Louvain, 1348, Louvain-la-Neuve, Belgium
| | - Maaike Vandermosten
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium; Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium; KU Leuven Child and Youth Institute, 3000, Leuven, Belgium.
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16
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Oliveira R, De Lucia M, Lutti A. Single-subject electroencephalography measurement of interhemispheric transfer time for the in-vivo estimation of axonal morphology. Hum Brain Mapp 2023; 44:4859-4874. [PMID: 37470446 PMCID: PMC10472916 DOI: 10.1002/hbm.26420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 06/12/2023] [Accepted: 06/26/2023] [Indexed: 07/21/2023] Open
Abstract
Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject-specific IHTTs are computed in a data-driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject-specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between-session variability was comparable to between-subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 μm across subjects. The change in axonal g-ratio with axonal radius ranged from 0.62 to 0.81 μm-α . The single-subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single-subject axonal morphology estimates.
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Affiliation(s)
- Rita Oliveira
- Laboratory for Research in Neuroimaging, Department of Clinical NeuroscienceLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Marzia De Lucia
- Laboratory for Research in Neuroimaging, Department of Clinical NeuroscienceLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical NeuroscienceLausanne University Hospital and University of LausanneLausanneSwitzerland
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17
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Shaterian Mohammadi H, Moazamian D, Athertya JS, Shin SH, Lo J, Suprana A, Malhi BS, Ma Y. Quantitative myelin water imaging using short TR adiabatic inversion recovery prepared echo-planar imaging (STAIR-EPI) sequence. FRONTIERS IN RADIOLOGY 2023; 3:1263491. [PMID: 37840897 PMCID: PMC10568074 DOI: 10.3389/fradi.2023.1263491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 09/18/2023] [Indexed: 10/17/2023]
Abstract
Introduction Numerous techniques for myelin water imaging (MWI) have been devised to specifically assess alterations in myelin. The biomarker employed to measure changes in myelin content is known as the myelin water fraction (MWF). The short TR adiabatic inversion recovery (STAIR) sequence has recently been identified as a highly effective method for calculating MWF. The purpose of this study is to develop a new clinical transitional myelin water imaging (MWI) technique that combines STAIR preparation and echo-planar imaging (EPI) (STAIR-EPI) sequence for data acquisition. Methods Myelin water (MW) in the brain has shorter T1 and T2 relaxation times than intracellular and extracellular water. In the proposed STAIR-EPI sequence, a short TR (e.g., ≤300 ms) together with an optimized inversion time enable robust long T1 water suppression with a wide range of T1 values [i.e., (600, 2,000) ms]. The EPI allows fast data acquisition of the remaining MW signals. Seven healthy volunteers and seven patients with multiple sclerosis (MS) were recruited and scanned in this study. The apparent myelin water fraction (aMWF), defined as the signal ratio of MW to total water, was measured in the lesions and normal-appearing white matter (NAWM) in MS patients and compared with those measured in the normal white matter (NWM) in healthy volunteers. Results As seen in the STAIR-EPI images acquired from MS patients, the MS lesions show lower signal intensities than NAWM do. The aMWF measurements for both MS lesions (3.6 ± 1.3%) and NAWM (8.6 ± 1.2%) in MS patients are significantly lower than NWM (10 ± 1.3%) in healthy volunteers (P < 0.001). Discussion The proposed STAIR-EPI technique, which can be implemented in MRI scanners from all vendors, is able to detect myelin loss in both MS lesions and NAWM in MS patients.
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Affiliation(s)
| | | | | | | | | | | | | | - Yajun Ma
- Department of Radiology, University of California San Diego, San Diego, CA, United States
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18
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Şişman M, Nguyen TD, Roberts AG, Romano DJ, Dimov AV, Kovanlikaya I, Spincemaille P, Wang Y. Microstructure-Informed Myelin Mapping (MIMM) from Gradient Echo MRI using Stochastic Matching Pursuit. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.22.23295993. [PMID: 37808826 PMCID: PMC10557811 DOI: 10.1101/2023.09.22.23295993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Quantification of the myelin content of the white matter is important for studying demyelination in neurodegenerative diseases such as Multiple Sclerosis (MS), particularly for longitudinal monitoring. A novel noninvasive MRI method, called Microstructure-Informed Myelin Mapping (MIMM), is developed to quantify the myelin volume fraction (MVF) by utilizing a multi gradient echo sequence (mGRE) and a detailed biophysical model of tissue microstructure. Myelin is modeled as anisotropic negative susceptibility source based on the Hollow Cylindrical Fiber Model (HCFM), and iron as isotropic positive susceptibility source in the extracellular region. Voxels with a range of biophysical parameters are simulated to create a dictionary of MR echo time magnitude signals and total susceptibility values. MRI signals measured using a mGRE sequence are then matched voxel-by-voxel to the created dictionary to obtain the spatial distributions of myelin and iron. Three different MIMM versions are presented to deal with the fiber orientation dependent susceptibility effects of the myelin sheaths: a basic variation, which assumes fiber orientation is an unknown to fit, two orientation informed variations, which assume the fiber orientation distribution is available either from a separate diffusion tensor imaging (DTI) acquisition or from a DTI atlas based fiber orientation map. While all showed a significant linear correlation with the reference method based on T2-relaxometry (p < 0.0001), DTI orientation informed and atlas orientation informed variations reduced overestimation at white matter tracts compared to the basic variation. Finally, the implications and usefulness of attaining an additional iron susceptibility distribution map are discussed. Highlights novel stochastic matching pursuit algorithm called microstructure-informed myelin mapping (MIMM) is developed to quantify Myelin Volume Fraction (MVF) using Magnetic Resonance Imaging (MRI) and microstructural modeling.utilizes a detailed biophysical model to capture the susceptibility effects on both magnitude and phase to quantify myelin and iron.matter fiber orientation effects are considered for the improved MVF quantification in the major fiber tracts.acquired myelin and iron maps may be utilized to monitor longitudinal disease progress.
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19
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Gong Z, Khattar N, Kiely M, Triebswetter C, Bouhrara M. REUSED: A deep neural network method for rapid whole-brain high-resolution myelin water fraction mapping from extremely under-sampled MRI. Comput Med Imaging Graph 2023; 108:102282. [PMID: 37586261 PMCID: PMC10528830 DOI: 10.1016/j.compmedimag.2023.102282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 07/23/2023] [Accepted: 07/24/2023] [Indexed: 08/18/2023]
Abstract
Changes in myelination are a cardinal feature of brain development and the pathophysiology of several central nervous system diseases, including multiple sclerosis and dementias. Advanced magnetic resonance imaging (MRI) methods have been developed to probe myelin content through the measurement of myelin water fraction (MWF). However, the prolonged data acquisition and post-processing times of current MWF mapping methods pose substantial hurdles to their clinical implementation. Recently, fast steady-state MRI sequences have been implemented to produce high-spatial resolution whole-brain MWF mapping within ∼20 min. Despite the subsequent significant advances in the inversion algorithm to derive MWF maps from steady-state MRI, the high-dimensional nature of such inversion does not permit further reduction of the acquisition time by data under-sampling. In this work, we present an unprecedented reduction in the computation (∼30 s) and the acquisition time (∼7 min) required for whole-brain high-resolution MWF mapping through a new Neural Network (NN)-based approach, named NN-Relaxometry of Extremely Under-SamplEd Data (NN-REUSED). Our analyses demonstrate virtually similar accuracy and precision in derived MWF values using NN-REUSED compared to results derived from the fully sampled reference method. The reduction in the acquisition and computation times represents a breakthrough toward clinically practical MWF mapping.
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Affiliation(s)
- Zhaoyuan Gong
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
| | | | - Matthew Kiely
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Curtis Triebswetter
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Mustapha Bouhrara
- Magnetic Resonance Physics of Aging and Dementia Unit, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
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20
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Baadsvik EL, Weiger M, Froidevaux R, Faigle W, Ineichen BV, Pruessmann KP. Quantitative magnetic resonance mapping of the myelin bilayer reflects pathology in multiple sclerosis brain tissue. SCIENCE ADVANCES 2023; 9:eadi0611. [PMID: 37566661 PMCID: PMC10421026 DOI: 10.1126/sciadv.adi0611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 07/07/2023] [Indexed: 08/13/2023]
Abstract
Multiple sclerosis (MS) is a neuroinflammatory disease characterized by loss of myelin (demyelination) and, to a certain extent, subsequent myelin repair (remyelination). To better understand the pathomechanisms underlying de- and remyelination and to monitor the efficacy of treatments aimed at regenerating myelin, techniques offering noninvasive visualizations of myelin are warranted. Magnetic resonance (MR) imaging has long been at the forefront of efforts to visualize myelin, but it has only recently become feasible to access the rapidly decaying resonance signals stemming from the myelin lipid-protein bilayer itself. Here, we show that direct MR mapping of the bilayer yields highly specific myelin maps in brain tissue from patients with MS. Furthermore, examination of the bilayer signal behavior is found to reveal pathological alterations in normal-appearing white and gray matter. These results indicate promise for in vivo implementations of the myelin bilayer mapping technique, with prospective applications in basic research, diagnostics, disease monitoring, and drug development.
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Affiliation(s)
- Emily Louise Baadsvik
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Markus Weiger
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Romain Froidevaux
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Wolfgang Faigle
- Neuroimmunology and MS Research Section, Neurology Clinic, University of Zurich, University Hospital Zurich, Zurich, Switzerland
- Institut Curie, Immunity and Cancer Unit 932, Paris, France
| | - Benjamin V. Ineichen
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Center for Reproducible Science, University of Zurich, Zurich, Switzerland
| | - Klaas P. Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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21
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Endt S, Engel M, Naldi E, Assereto R, Molendowska M, Mueller L, Mayrink Verdun C, Pirkl CM, Palombo M, Jones DK, Menzel MI. In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods. APPLIED MAGNETIC RESONANCE 2023; 54:1571-1588. [PMID: 38037641 PMCID: PMC10682074 DOI: 10.1007/s00723-023-01584-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/18/2023] [Accepted: 07/25/2023] [Indexed: 12/02/2023]
Abstract
Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.
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Affiliation(s)
- Sebastian Endt
- Technical University of Munich, Munich, Germany
- AImotion Bavaria, Technische Hochschule Ingolstadt, Ingolstadt, Germany
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Maria Engel
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Emanuele Naldi
- Technische Universität Braunschweig, Braunschweig, Germany
| | | | - Malwina Molendowska
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Medical Radiation Physics, Lund University, Lund, Sweden
| | - Lars Mueller
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM), University of Leeds, Leeds, United Kingdom
| | - Claudio Mayrink Verdun
- Technical University of Munich, Munich, Germany
- Munich Center for Machine Learning, Munich, Germany
| | | | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Marion I. Menzel
- Technical University of Munich, Munich, Germany
- AImotion Bavaria, Technische Hochschule Ingolstadt, Ingolstadt, Germany
- GE HealthCare, Munich, Germany
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22
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Alsameen MH, Gong Z, Qian W, Kiely M, Triebswetter C, Bergeron CM, Cortina LE, Faulkner ME, Laporte JP, Bouhrara M. C-NODDI: a constrained NODDI model for axonal density and orientation determinations in cerebral white matter. Front Neurol 2023; 14:1205426. [PMID: 37602266 PMCID: PMC10435293 DOI: 10.3389/fneur.2023.1205426] [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: 04/13/2023] [Accepted: 07/14/2023] [Indexed: 08/22/2023] Open
Abstract
Purpose Neurite orientation dispersion and density imaging (NODDI) provides measures of neurite density and dispersion through computation of the neurite density index (NDI) and the orientation dispersion index (ODI). However, NODDI overestimates the cerebrospinal fluid water fraction in white matter (WM) and provides physiologically unrealistic high NDI values. Furthermore, derived NDI values are echo-time (TE)-dependent. In this work, we propose a modification of NODDI, named constrained NODDI (C-NODDI), for NDI and ODI mapping in WM. Methods Using NODDI and C-NODDI, we investigated age-related alterations in WM in a cohort of 58 cognitively unimpaired adults. Further, NDI values derived using NODDI or C-NODDI were correlated with the neurofilament light chain (NfL) concentration levels, a plasma biomarker of axonal degeneration. Finally, we investigated the TE dependence of NODDI or C-NODDI derived NDI and ODI. Results ODI derived values using both approaches were virtually identical, exhibiting constant trends with age. Further, our results indicated a quadratic relationship between NDI and age suggesting that axonal maturation continues until middle age followed by a decrease. This quadratic association was notably significant in several WM regions using C-NODDI, while limited to a few regions using NODDI. Further, C-NODDI-NDI values exhibited a stronger correlation with NfL concentration levels as compared to NODDI-NDI, with lower NDI values corresponding to higher levels of NfL. Finally, we confirmed the previous finding that NDI estimation using NODDI was dependent on TE, while NDI derived values using C-NODDI exhibited lower sensitivity to TE in WM. Conclusion C-NODDI provides a complementary method to NODDI for determination of NDI in white matter.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
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23
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Pérez-Cervera L, De Santis S, Marcos E, Ghorbanzad-Ghaziany Z, Trouvé-Carpena A, Selim MK, Pérez-Ramírez Ú, Pfarr S, Bach P, Halli P, Kiefer F, Moratal D, Kirsch P, Sommer WH, Canals S. Alcohol-induced damage to the fimbria/fornix reduces hippocampal-prefrontal cortex connection during early abstinence. Acta Neuropathol Commun 2023; 11:101. [PMID: 37344865 PMCID: PMC10286362 DOI: 10.1186/s40478-023-01597-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 05/30/2023] [Indexed: 06/23/2023] Open
Abstract
INTRODUCTION Alcohol dependence is characterized by a gradual reduction in cognitive control and inflexibility to contingency changes. The neuroadaptations underlying this aberrant behavior are poorly understood. Using an animal model of alcohol use disorders (AUD) and complementing diffusion-weighted (dw)-MRI with quantitative immunohistochemistry and electrophysiological recordings, we provide causal evidence that chronic intermittent alcohol exposure affects the microstructural integrity of the fimbria/fornix, decreasing myelin basic protein content, and reducing the effective communication from the hippocampus (HC) to the prefrontal cortex (PFC). Using a simple quantitative neural network model, we show how disturbed HC-PFC communication may impede the extinction of maladaptive memories, decreasing flexibility. Finally, combining dw-MRI and psychometric data in AUD patients, we discovered an association between the magnitude of microstructural alteration in the fimbria/fornix and the reduction in cognitive flexibility. Overall, these findings highlight the vulnerability of the fimbria/fornix microstructure in AUD and its potential contribution to alcohol pathophysiology. Fimbria vulnerability to alcohol underlies hippocampal-prefrontal cortex dysfunction and correlates with cognitive impairment.
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Affiliation(s)
- Laura Pérez-Cervera
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
| | - Silvia De Santis
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
| | - Encarni Marcos
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
| | - Zahra Ghorbanzad-Ghaziany
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
- Radiation Science and Biomedical Imaging, University of Sherbrooke, Sherbrooke, Québec, Canada
| | - Alejandro Trouvé-Carpena
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
| | - Mohamed Kotb Selim
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain
| | - Úrsula Pérez-Ramírez
- Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain
| | - Simone Pfarr
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Patrick Bach
- Department of Addiction Medicine, Department of Clinical Psychology, Medical Faculty Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Patrick Halli
- Department of Psychology, University of Heidelberg, Heidelberg, Germany
| | - Falk Kiefer
- Department of Addiction Medicine, Department of Clinical Psychology, Medical Faculty Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - David Moratal
- Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain
| | - Peter Kirsch
- Department of Psychology, University of Heidelberg, Heidelberg, Germany
| | - Wolfgang H Sommer
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical faculty Mannheim, University of Heidelberg, Mannheim, Germany.
- Department of Addiction Medicine, Department of Clinical Psychology, Medical Faculty Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany.
| | - Santiago Canals
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas and Universidad Miguel Hernández, Sant Joan d'Alacant, Alicante, Spain.
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24
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Scheinok TJ, D'Haeseleer M, Nagels G, De Bundel D, Van Schependom J. Neuronal activity and NIBS in developmental myelination and remyelination - current state of knowledge. Prog Neurobiol 2023; 226:102459. [PMID: 37127087 DOI: 10.1016/j.pneurobio.2023.102459] [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: 02/06/2023] [Revised: 04/06/2023] [Accepted: 04/28/2023] [Indexed: 05/03/2023]
Abstract
Oligodendrocytes are responsible for myelinating central nervous system (CNS) axons. and rapid electrical transmission through saltatory conduction of action potentials. Myelination and myelin repair rely partially on oligodendrogenesis, which comprises. oligodendrocyte precursor cell (OPC) migration, maturation, and differentiation into. oligodendrocytes (OL). In multiple sclerosis (MS), demyelination occurs due to an. inflammatory cascade with auto-reactive T-cells. When oligodendrogenesis fails, remyelination becomes aberrant and conduction impairments are no longer restored. Although current disease modifying therapies have achieved results in modulating the. faulty immune response, disease progression continues because of chronic. inflammation, neurodegeneration, and failure of remyelination. Therapies have been. tried to promote remyelination. Modulation of neuronal activity seems to be a very. promising strategy in preclinical studies. Additionally, studies in people with MS. (pwMS) have shown symptom improvement following non-invasive brain stimulation. (NIBS) techniques. The aforementioned mechanisms are yet unknown and probably. involve both the activation of neurons and glial cells. Noting neuronal activity. contributes to myelin plasticity and that NIBS modulates neuronal activity; we argue. that NIBS is a promising research horizon for demyelinating diseases. We review the. hypothesized pathways through which NIBS may affect both neuronal activity in the. CNS and how the resulting activity can affect oligodendrogenesis and myelination.
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Affiliation(s)
- Thomas J Scheinok
- AIMS Lab, Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussel, Belgium; Department of Pharmaceutical and Pharmacological Sciences, Research Group Experimental Pharmacology (EFAR), Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussels, Belgium.
| | - Miguel D'Haeseleer
- Nationaal Multiple Sclerose Centrum, Vanheylenstraat 16, 1820 Melsbroek, Belgium
| | - Guy Nagels
- AIMS Lab, Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussel, Belgium; St Edmund Hall, University of Oxford, Queen's Lane, Oxford, UK
| | - Dimitri De Bundel
- Department of Pharmaceutical and Pharmacological Sciences, Research Group Experimental Pharmacology (EFAR), Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussels, Belgium
| | - Jeroen Van Schependom
- AIMS Lab, Center for Neurosciences, UZ Brussel, Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussel, Belgium; Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussel, Belgium
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25
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Kai J, Mackinley M, Khan AR, Palaniyappan L. Aberrant frontal lobe "U"-shaped association fibers in first-episode schizophrenia: A 7-Tesla Diffusion Imaging Study. Neuroimage Clin 2023; 38:103367. [PMID: 36913907 PMCID: PMC10011060 DOI: 10.1016/j.nicl.2023.103367] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 02/08/2023] [Accepted: 03/01/2023] [Indexed: 03/07/2023]
Abstract
Schizophrenia is believed to be a developmental disorder with one hypothesis suggesting that symptoms arise due to abnormal interactions (or disconnectivity) between different brain regions. While some major deep white matter pathways have been extensively studied (e.g. arcuate fasciculus), studies of short-ranged, "U"-shaped tracts have been limited in patients with schizophrenia, in part due to the sheer abundance of tracts present and due to the spatial variations across individuals that defy probabilistic characterization in the absence of reliable templates. In this study, we use diffusion magnetic resonance imaging (dMRI) to investigate frontal lobe superficial white matter that are present in the majority of study participants, comparing healthy controls and minimally treated patients with first-episode schizophrenia (<3 median days of lifetime treatment). Through group comparisons, 3 out of 63 frontal lobe "U"-shaped tracts were found to demonstrate localized aberrations affecting the microstructural tissue properties (via diffusion tensor metrics) in this early stage of disease. No associations were found in patients between aberrant segments of affected tracts and clinical or cognitive variables. Aberrations in the frontal lobe "U"-shaped tracts in early untreated stages of psychosis occur irrespective of symptom burden, and are distributed across critical functional networks associated with executive function and salience processing. While we limited the investigation to the frontal lobe, a framework has been developed to study such connections in other brain regions, enabling further extensive investigations jointly with the major deep white matter pathways.
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Affiliation(s)
- Jason Kai
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada; Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Michael Mackinley
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada
| | - Ali R Khan
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada; Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Lena Palaniyappan
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada; Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada; Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
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26
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Johnson P, Vavasour IM, Stojkova BJ, Abel S, Lee LE, Laule C, Tam R, Li DKB, Ackermans N, Schabas AJ, Chan J, Cross H, Sayao AL, Devonshire V, Carruthers R, Traboulsee A, Kolind SH. Myelin heterogeneity for assessing normal appearing white matter myelin damage in multiple sclerosis. J Neuroimaging 2023; 33:227-234. [PMID: 36443960 DOI: 10.1111/jon.13069] [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: 06/16/2022] [Revised: 11/04/2022] [Accepted: 11/08/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND AND PURPOSE Conventional MRI measures of multiple sclerosis (MS) disease severity, such as lesion volume and brain atrophy, do not provide information about microstructural tissue changes, which may be driving physical and cognitive progression. Myelin damage in normal-appearing white matter (NAWM) is likely an important contributor to MS disability. Myelin water fraction (MWF) provides quantitative measurements of myelin. Mean MWF reflects average myelin content, while MWF standard deviation (SD) describes variation in myelin within regions. The myelin heterogeneity index (MHI = SD/mean MWF) is a composite metric of myelin content and myelin variability. We investigated how mean MWF, SD, and MHI compare in differentiating MS from controls and their associations with physical and cognitive disability. METHODS Myelin water imaging data were acquired from 91 MS participants and 31 healthy controls (HC). Segmented whole-brain NAWM and corpus callosum (CC) NAWM, mean MWF, SD, and MHI were compared between groups. Associations of mean MWF, SD, and MHI with Expanded Disability Status Scale and Symbol Digit Modalities Test were assessed. RESULTS NAWM and CC MHI had the highest area under the curve: .78 (95% confidence interval [CI]: .69, .86) and .84 (95% CI: .76, .91), respectively, distinguishing MS from HC. CONCLUSIONS Mean MWF, SD, and MHI provide complementary information when assessing regional and global NAWM abnormalities in MS and associations with clinical outcome measures. Examining all three metrics (mean MWF, SD, and MHI) enables a more detailed interpretation of results, depending on whether regions of interest include areas that are more heterogeneous, earlier in the demyelination process, or uniformly injured.
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Affiliation(s)
- Poljanka Johnson
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Irene M Vavasour
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Shawna Abel
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Lisa Eunyoung Lee
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Roger Tam
- School of Biomedical Engineering, University of British Columbia, Vancouver, British Columbia, Canada
| | - David K B Li
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Nathalie Ackermans
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Alice J Schabas
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Jillian Chan
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Helen Cross
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Ana-Luiza Sayao
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Virginia Devonshire
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Robert Carruthers
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Anthony Traboulsee
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Shannon H Kolind
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair and Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
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27
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Kelly KJ, Hutton JS, Parikh NA, Barnes-Davis ME. Neuroimaging of brain connectivity related to reading outcomes in children born preterm: A critical narrative review. Front Pediatr 2023; 11:1083364. [PMID: 36937974 PMCID: PMC10014573 DOI: 10.3389/fped.2023.1083364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 02/06/2023] [Indexed: 03/06/2023] Open
Abstract
Premature children are at high risk for delays in language and reading, which can lead to poor school achievement. Neuroimaging studies have assessed structural and functional connectivity by diffusion MRI, functional MRI, and magnetoencephalography, in order to better define the "reading network" in children born preterm. Findings point to differences in structural and functional connectivity compared to children born at term. It is not entirely clear whether this discrepancy is due to delayed development or alternative mechanisms for reading, which may have developed to compensate for brain injury in the perinatal period. This narrative review critically appraises the existing literature evaluating the neural basis of reading in preterm children, summarizes the current findings, and suggests future directions in the field.
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Affiliation(s)
- Kaitlyn J. Kelly
- Division of Neonatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - John S. Hutton
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
- Division of General & Community Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
| | - Nehal A. Parikh
- Division of Neonatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Maria E. Barnes-Davis
- Division of Neonatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
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28
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Walker KA, Duggan MR, Gong Z, Dark HE, Laporte JP, Faulkner ME, An Y, Lewis A, Moghekar AR, Resnick SM, Bouhrara M. MRI and fluid biomarkers reveal determinants of myelin and axonal loss with aging. Ann Clin Transl Neurol 2023; 10:397-407. [PMID: 36762407 PMCID: PMC10014005 DOI: 10.1002/acn3.51730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/15/2022] [Accepted: 12/31/2022] [Indexed: 02/11/2023] Open
Abstract
OBJECTIVE White matter damage is a feature of Alzheimer's disease, yet little is known about how facets of the Alzheimer's disease process relate to key features of white matter structure. We examined the association of Alzheimer's disease (Aß42/40 ratio; pTau181), neuronal injury (NfL), and reactive astrogliosis (GFAP) biomarkers with MRI measures of myelin content and axonal density. METHODS Among cognitively normal participants in the BLSA and GESTALT studies who received MRI measures of myelin content (defined by myelin water fraction [MWF]) and axonal density (defined by neurite density index [NDI]), we quantified plasma levels of Aβ42 , Aβ40 , pTau181, NfL, and GFAP. Linear regression models adjusted for demographic variables were used to relate these plasma biomarker levels to the MRI measures. RESULTS In total, 119 participants received MWF imaging (age: 56 [SD 21]), of which 43 received NDI imaging (age: 50 [SD 18]). We found no relationship between plasma biomarkers and total brain myelin content. However, secondary analysis found higher GFAP was associated with lower MWF in the temporal lobes (ß = -0.13; P = 0.049). Further, higher levels of NfL (ß = -0.22; P = 0.009) and GFAP (ß = -0.29; P = 0.002) were associated with lower total brain axonal density. Secondary analyses found lower Aβ42/40 ratio and higher pTau181 were also associated with lower axonal density, but only in select brain regions. These results remained similar after additionally adjusting for cardiovascular risk factors. INTERPRETATION Plasma biomarkers of neuronal injury and astrogliosis are associated with reduced axonal density and region-specific myelin content. Axonal loss and demyelination may co-occur with neurodegeneration and astrogliosis ahead of clinically meaningful cognitive decline.
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Affiliation(s)
- Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Michael R Duggan
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Heather E Dark
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - John P Laporte
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Mary E Faulkner
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Alexandria Lewis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, 21224
| | - Abhay R Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, 21224
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
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29
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Lee S, Shin HG, Kim M, Lee J. Depth-wise profiles of iron and myelin in the cortex and white matter using χ-separation: A preliminary study. Neuroimage 2023; 273:120058. [PMID: 36997135 DOI: 10.1016/j.neuroimage.2023.120058] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 03/26/2023] [Accepted: 03/27/2023] [Indexed: 03/30/2023] Open
Abstract
The in-vivo profiling of iron and myelin across cortical depths and underlying white matter has important implications for advancing knowledge about their roles in brain development and degeneration. Here, we utilize χ-separation, a recently-proposed advanced susceptibility mapping that creates positive (χpos) and negative (χneg) susceptibility maps, to generate the depth-wise profiles of χpos and χneg as surrogate biomarkers for iron and myelin, respectively. Two regional sulcal fundi of precentral and middle frontal areas are profiled and compared with findings from previous studies. The results show that the χpos profiles peak at superificial white matter (SWM), which is an area beneath cortical gray matter known to have the highest accumulation of iron within the cortex and white matter. On the other hand, the χneg profiles increase in SWM toward deeper white matter. These characteristics in the two profiles are in agreement with histological findings of iron and myelin. Furthermore, the χneg profiles report regional differences that agree with well-known distributions of myelin concentration. When the two profiles are compared with those of QSM and R2*, different shapes and peak locations are observed. This preliminary study offers an insight into one of the possible applications of χ-separation for exploring microstructural information of the human brain, as well as clinical applications in monitoring changes of iron and myelin in related diseases.
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30
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Boa Sorte Silva NC, Dao E, Liang Hsu C, Tam RC, Lam K, Alkeridy W, Laule C, Vavasour IM, Stein RG, Liu-Ambrose T. Myelin and Physical Activity in Older Adults With Cerebral Small Vessel Disease and Mild Cognitive Impairment. J Gerontol A Biol Sci Med Sci 2023; 78:545-553. [PMID: 35876839 DOI: 10.1093/gerona/glac149] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Myelin loss is a feature of cerebral small vessel disease (cSVD). Although physical activity levels may exert protective effects over cSVD pathology, its specific relationship with myelin content in people living with the cSVD is unknown. Thus, we investigated whether physical activity levels are associated with myelin in community-dwelling older adults with cSVD and mild cognitive impairment. METHODS Cross-sectional data from 102 individuals with cSVD and mild cognitive impairment were analyzed (mean age [SD] = 74.7 years [5.5], 63.7% female). Myelin was measured using a magnetic resonance gradient and spin echo sequence. Physical activity was estimated using the Physical Activity Scale for the Elderly. Hierarchical regression models adjusting for total intracranial volume, age, sex, body mass index, and education were conducted to determine the associations between myelin content and physical activity. Significant models were further adjusted for white matter hyperintensity volume. RESULTS In adjusted models, greater physical activity was linked to higher myelin content in the whole-brain white matter (R2change = .04, p = .048). Greater physical activity was also associated with myelin content in the sagittal stratum (R2change = .08, p = .004), anterior corona radiata (R2change = .04, p = .049), and genu of the corpus callosum (R2change = .05, p = .018). Adjusting for white matter hyperintensity volume did not change any of these associations. CONCLUSIONS Physical activity may be a strategy to maintain myelin in older adults with cSVD and mild cognitive impairment. Future randomized controlled trials of exercise are needed to determine whether exercise increases myelin content.
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Affiliation(s)
- Nárlon C Boa Sorte Silva
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
| | - Elizabeth Dao
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Chun Liang Hsu
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, Massachusetts, USA
| | - Roger C Tam
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,School of Biomedical Engineering, Faculty of Applied Science and Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Kevin Lam
- Department of Medicine, Division of Neurology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Walid Alkeridy
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Medicine, King Saud University, College of Medicine, Riyadh, Saudi Arabia.,Department of Medicine, Division of Geriatrics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Irene M Vavasour
- Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Ryan G Stein
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
| | - Teresa Liu-Ambrose
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Centre for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
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Baadsvik EL, Weiger M, Froidevaux R, Faigle W, Ineichen BV, Pruessmann KP. Mapping the myelin bilayer with short-T 2 MRI: Methods validation and reference data for healthy human brain. Magn Reson Med 2023; 89:665-677. [PMID: 36253953 PMCID: PMC10091754 DOI: 10.1002/mrm.29481] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/24/2022] [Accepted: 09/20/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE To explore the properties of short-T2 signals in human brain, investigate the impact of various experimental procedures on these properties and evaluate the performance of three-component analysis. METHODS Eight samples of non-pathological human brain tissue were subjected to different combinations of experimental procedures including D2 O exchange and frozen storage. Short-T2 imaging techniques were employed to acquire multi-TE (33-2067 μs) data, to which a three-component complex model was fitted in two steps to recover the properties of the underlying signal components and produce amplitude maps of each component. For validation of the component amplitude maps, the samples underwent immunohistochemical myelin staining. RESULTS The signal component representing the myelin bilayer exhibited super-exponential decay with T2,min of 5.48 μs and a chemical shift of 1.07 ppm, and its amplitude could be successfully mapped in both white and gray matter in all samples. These myelin maps corresponded well to myelin-stained tissue sections. Gray matter signals exhibited somewhat different components than white matter signals, but both tissue types were well represented by the signal model. Frozen tissue storage did not alter the signal components but influenced component amplitudes. D2 O exchange was necessary to characterize the non-aqueous signal components, but component amplitude mapping could be reliably performed also in the presence of H2 O signals. CONCLUSIONS The myelin mapping approach explored here produced reasonable and stable results for all samples. The extensive tissue and methodological investigations performed in this work form a basis for signal interpretation in future studies both ex vivo and in vivo.
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Affiliation(s)
- Emily Louise Baadsvik
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Markus Weiger
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Romain Froidevaux
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Wolfgang Faigle
- Neuroimmunology and MS Research Section, Neurology Clinic, University of Zurich, University Hospital Zurich, Zurich, Switzerland
| | - Benjamin Victor Ineichen
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Klaas Paul Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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Filimonova E, Amelina E, Sazonova A, Zaitsev B, Rzaev J. Assessment of normal myelination in infants and young children using the T1w/T2w mapping technique. Front Neurosci 2023; 17:1102691. [PMID: 36925743 PMCID: PMC10011126 DOI: 10.3389/fnins.2023.1102691] [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: 11/19/2022] [Accepted: 02/13/2023] [Indexed: 03/04/2023] Open
Abstract
Background White matter myelination is a crucial process of CNS maturation. The purpose of this study was to validate the T1w/T2w mapping technique for brain myelination assessment in infants and young children. Methods Ninety-four patients (0-23 months of age) without structural abnormalities on brain MRI were evaluated by using the T1w/T2w mapping method. The T1w/T2w signal intensity ratio, which reflects white matter integrity and the degree of myelination, was calculated in various brain regions. We performed a Pearson correlation analysis, a LOESS regression analysis, and a 2nd order polynomial regression analysis to describe the relationships between the regional metrics and the age of the patients (in months). Results T1w/T2w ratio values rapidly increased in the first 6-9 months of life and then slowed thereafter. The T1w/T2w mapping technique emphasized the contrast between myelinated and less myelinated structures in all age groups, which resulted in better visualization. There were strong positive correlations between the T1w/T2w ratio values from the majority of white matter ROIs and the subjects' age (R = 0.7-0.9, p < 0.001). Within all of the analyzed regions, there were non-linear relationships between age and T1/T2 ratio values that varied by anatomical and functional location. Regions such as the splenium and the genu of the corpus callosum showed the highest R2 values, thus indicating less scattering of data and a better fit to the model. Conclusion The T1w/T2w mapping technique may enhance our diagnostic ability to assess myelination patterns in the brains of infants and young children.
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Affiliation(s)
- Elena Filimonova
- Federal Center of Neurosurgery, Novosibirsk, Russia.,Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
| | - Evgenia Amelina
- Stream Data Analytics and Machine Learning Laboratory, Novosibirsk State University, Novosibirsk, Russia
| | - Aleksandra Sazonova
- Federal Center of Neurosurgery, Novosibirsk, Russia.,Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia
| | - Boris Zaitsev
- Federal Center of Neurosurgery, Novosibirsk, Russia.,Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia
| | - Jamil Rzaev
- Federal Center of Neurosurgery, Novosibirsk, Russia.,Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia.,Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia
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Bi C, Ou MY, Bouhrara M, Spencer RG. Span of regularization for solution of inverse problems with application to magnetic resonance relaxometry of the brain. Sci Rep 2022; 12:20194. [PMID: 36418516 PMCID: PMC9684479 DOI: 10.1038/s41598-022-22739-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 10/19/2022] [Indexed: 11/25/2022] Open
Abstract
We present a new regularization method for the solution of the Fredholm integral equation (FIE) of the first kind, in which we incorporate solutions corresponding to a range of Tikhonov regularizers into the end result. This method identifies solutions within a much larger function space, spanned by this set of regularized solutions, than is available to conventional regularization methods. An additional key development is the use of dictionary functions derived from noise-corrupted inversion of the discretized FIE. In effect, we combine the stability of solutions with greater degrees of regularization with the resolution of those that are less regularized. The span of regularizations (SpanReg) method may be widely applicable throughout the field of inverse problems.
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Affiliation(s)
- Chuan Bi
- grid.411024.20000 0001 2175 4264Department of Psychiatry, University of Maryland, Baltimore, Baltimore, MD 21201 USA
| | - M. Yvonne Ou
- grid.33489.350000 0001 0454 4791Department of Mathematical Sciences, University of Delaware, Newark, DE 19716 USA
| | - Mustapha Bouhrara
- grid.94365.3d0000 0001 2297 5165National Institute on Aging, National Institutes of Health, Baltimore, MD 21224 USA
| | - Richard G. Spencer
- grid.94365.3d0000 0001 2297 5165National Institute on Aging, National Institutes of Health, Baltimore, MD 21224 USA
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Kim W, Shin HG, Lee H, Park D, Kang J, Nam Y, Lee J, Jang J. χ-Separation Imaging for Diagnosis of Multiple Sclerosis versus Neuromyelitis Optica Spectrum Disorder. Radiology 2022; 307:e220941. [PMID: 36413128 DOI: 10.1148/radiol.220941] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Background Use of χ-separation imaging can provide surrogates for iron and myelin that relate closely to abnormal changes in multiple sclerosis (MS) lesions. Purpose To evaluate the appearances of MS and neuromyelitis optica spectrum disorder (NMOSD) brain lesions on χ-separation maps and explore their diagnostic value in differentiating the two diseases in comparison with previously reported diagnostic criteria. Materials and Methods This prospective study included individuals with MS or NMOSD who underwent χ-separation imaging from October 2017 to October 2020. Positive (χpos) and negative (χneg) susceptibility were estimated separately by using local frequency shifts and calculating R2' (R2' = R2* - R2). R2 mapping was performed with a machine learning approach. For each lesion, presence of the central vein sign (CVS) and paramagnetic rim sign (PRS) and signal characteristics on χneg and χpos maps were assessed and compared. For each participant, the proportion of lesions with CVS, PRS, and hypodiamagnetism was calculated. Diagnostic performances were assessed using receiver operating characteristic (ROC) curve analysis. Results A total of 32 participants with MS (mean age, 34 years ± 10 [SD]; 25 women, seven men) and 15 with NMOSD (mean age, 52 years ± 17; 14 women, one man) were evaluated, with a total of 611 MS and 225 NMOSD brain lesions. On the χneg maps, 80.2% (490 of 611) of MS lesions were categorized as hypodiamagnetic versus 13.8% (31 of 225) of NMOSD lesions (P < .001). Lesion appearances on the χpos maps showed no evidence of a difference between the two diseases. In per-participant analysis, participants with MS showed a higher proportion of hypodiamagnetic lesions (83%; IQR, 72-93) than those with NMOSD (6%; IQR, 0-14; P < .001). The proportion of hypodiamagnetic lesions achieved excellent diagnostic performance (area under the ROC curve, 0.96; 95% CI: 0.91, 1.00). Conclusion On χ-separation maps, multiple sclerosis (MS) lesions tend to be hypodiamagnetic, which can serve as an important hallmark to differentiate MS from neuromyelitis optica spectrum disorder. © RSNA, 2022 Supplemental material is available for this article.
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Affiliation(s)
- Woojun Kim
- From the Departments of Neurology (W.K.) and Radiology (H.L., D.P., J.J.), Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul 06591, Republic of Korea; Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea (H.G.S., J.L.); Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, Md (H.G.S.); F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Md (H.G.S.); and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (J.K., Y.N.)
| | - Hyeong-Geol Shin
- From the Departments of Neurology (W.K.) and Radiology (H.L., D.P., J.J.), Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul 06591, Republic of Korea; Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea (H.G.S., J.L.); Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, Md (H.G.S.); F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Md (H.G.S.); and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (J.K., Y.N.)
| | - Hyebin Lee
- From the Departments of Neurology (W.K.) and Radiology (H.L., D.P., J.J.), Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul 06591, Republic of Korea; Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea (H.G.S., J.L.); Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, Md (H.G.S.); F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Md (H.G.S.); and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (J.K., Y.N.)
| | - Dohoon Park
- From the Departments of Neurology (W.K.) and Radiology (H.L., D.P., J.J.), Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul 06591, Republic of Korea; Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea (H.G.S., J.L.); Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, Md (H.G.S.); F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Md (H.G.S.); and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (J.K., Y.N.)
| | - Junghwa Kang
- From the Departments of Neurology (W.K.) and Radiology (H.L., D.P., J.J.), Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul 06591, Republic of Korea; Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea (H.G.S., J.L.); Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, Md (H.G.S.); F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Md (H.G.S.); and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (J.K., Y.N.)
| | - Yoonho Nam
- From the Departments of Neurology (W.K.) and Radiology (H.L., D.P., J.J.), Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul 06591, Republic of Korea; Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea (H.G.S., J.L.); Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, Md (H.G.S.); F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Md (H.G.S.); and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (J.K., Y.N.)
| | - Jongho Lee
- From the Departments of Neurology (W.K.) and Radiology (H.L., D.P., J.J.), Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul 06591, Republic of Korea; Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea (H.G.S., J.L.); Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, Md (H.G.S.); F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Md (H.G.S.); and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (J.K., Y.N.)
| | - Jinhee Jang
- From the Departments of Neurology (W.K.) and Radiology (H.L., D.P., J.J.), Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Banpo-daero 222, Seocho-gu, Seoul 06591, Republic of Korea; Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea (H.G.S., J.L.); Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, Md (H.G.S.); F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Md (H.G.S.); and Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea (J.K., Y.N.)
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Hirschfeld LR, Risacher SL, Nho K, Saykin AJ. Myelin repair in Alzheimer's disease: a review of biological pathways and potential therapeutics. Transl Neurodegener 2022; 11:47. [PMID: 36284351 PMCID: PMC9598036 DOI: 10.1186/s40035-022-00321-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 10/15/2022] [Indexed: 11/29/2022] Open
Abstract
This literature review investigates the significant overlap between myelin-repair signaling pathways and pathways known to contribute to hallmark pathologies of Alzheimer's disease (AD). We discuss previously investigated therapeutic targets of amyloid, tau, and ApoE, as well as other potential therapeutic targets that have been empirically shown to contribute to both remyelination and progression of AD. Current evidence shows that there are multiple AD-relevant pathways which overlap significantly with remyelination and myelin repair through the encouragement of oligodendrocyte proliferation, maturation, and myelin production. There is a present need for a single, cohesive model of myelin homeostasis in AD. While determining a causative pathway is beyond the scope of this review, it may be possible to investigate the pathological overlap of myelin repair and AD through therapeutic approaches.
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Affiliation(s)
- Lauren Rose Hirschfeld
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Shannon L Risacher
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kwangsik Nho
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- School of Informatics and Computing, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA
| | - Andrew J Saykin
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
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36
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Combes AJ, Clarke MA, O'Grady KP, Schilling KG, Smith SA. Advanced spinal cord MRI in multiple sclerosis: Current techniques and future directions. Neuroimage Clin 2022; 36:103244. [PMID: 36306717 PMCID: PMC9668663 DOI: 10.1016/j.nicl.2022.103244] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 09/02/2022] [Accepted: 10/19/2022] [Indexed: 11/11/2022]
Abstract
Spinal cord magnetic resonance imaging (MRI) has a central role in multiple sclerosis (MS) clinical practice for diagnosis and disease monitoring. Advanced MRI sequences capable of visualizing and quantifying tissue macro- and microstructure and reflecting different pathological disease processes have been used in MS research; however, the spinal cord remains under-explored, partly due to technical obstacles inherent to imaging this structure. We propose that the study of the spinal cord merits equal ambition in overcoming technical challenges, and that there is much information to be exploited to make valuable contributions to our understanding of MS. We present a narrative review on the latest progress in advanced spinal cord MRI in MS, covering in the first part structural, functional, metabolic and vascular imaging methods. We focus on recent studies of MS and those making significant technical steps, noting the challenges that remain to be addressed and what stands to be gained from such advances. Throughout we also refer to other works that presend more in-depth review on specific themes. In the second part, we present several topics that, in our view, hold particular potential. The need for better imaging of gray matter is discussed. We stress the importance of developing imaging beyond the cervical spinal cord, and explore the use of ultra-high field MRI. Finally, some recommendations are given for future research, from study design to newer developments in analysis, and the need for harmonization of sequences and methods within the field. This review is aimed at researchers and clinicians with an interest in gaining an overview of the current state of advanced MRI research in this field and what is primed to be the future of spinal cord imaging in MS research.
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Affiliation(s)
- Anna J.E. Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Corresponding author at: 1161 21st Ave S, MCN AA1105, Nashville, TN 37232, USA.
| | - Margareta A. Clarke
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States
| | - Kristin P. O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
| | - Kurt G. Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States
| | - Seth A. Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN 37232-2310, United States,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Medical Center North, 1161 21st Ave. South, Nashville, TN 37232, United States,Department of Biomedical Engineering, Vanderbilt University, 2301 Vanderbilt Place, PMB 351826, Nashville, TN 37235-1826, United States
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Hill M, Cunniffe N, Franklin R. Seeing is believing: Identifying remyelination in the central nervous system. Curr Opin Pharmacol 2022; 66:102269. [DOI: 10.1016/j.coph.2022.102269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 06/20/2022] [Indexed: 11/03/2022]
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Jara H, Sakai O, Farrher E, Oros-Peusquens AM, Shah NJ, Alsop DC, Keenan KE. Primary Multiparametric Quantitative Brain MRI: State-of-the-Art Relaxometric and Proton Density Mapping Techniques. Radiology 2022; 305:5-18. [PMID: 36040334 PMCID: PMC9524578 DOI: 10.1148/radiol.211519] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 05/01/2022] [Accepted: 05/24/2022] [Indexed: 11/11/2022]
Abstract
This review on brain multiparametric quantitative MRI (MP-qMRI) focuses on the primary subset of quantitative MRI (qMRI) parameters that represent the mobile ("free") and bound ("motion-restricted") proton pools. Such primary parameters are the proton densities, relaxation times, and magnetization transfer parameters. Diffusion qMRI is also included because of its wide implementation in complete clinical MP-qMRI application. MP-qMRI advances were reviewed over the past 2 decades, with substantial progress observed toward accelerating image acquisition and increasing mapping accuracy. Areas that need further investigation and refinement are identified as follows: (a) the biologic underpinnings of qMRI parameter values and their changes with age and/or disease and (b) the theoretical limitations implicitly built into most qMRI mapping algorithms that do not distinguish between the different spatial scales of voxels versus spin packets, the central physical object of the Bloch theory. With rapidly improving image processing techniques and continuous advances in computer hardware, MP-qMRI has the potential for implementation in a wide range of clinical applications. Currently, three emerging MP-qMRI applications are synthetic MRI, macrostructural qMRI, and microstructural tissue modeling.
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Affiliation(s)
- Hernán Jara
- From the Department of Radiology, Boston University, 670 Albany St,
Boston, Mass 02118 (H.J., O.S.); Institute of Neuroscience and Medicine-4,
Forschungszentrum Jülich, Jülich, Germany (E.F., A.M.O.P.,
N.J.S.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard
Medical School, Boston, Mass (D.C.A.); and Physical Measurement Laboratory,
National Institute of Standards and Technology, Boulder, Colo (K.E.K.)
| | - Osamu Sakai
- From the Department of Radiology, Boston University, 670 Albany St,
Boston, Mass 02118 (H.J., O.S.); Institute of Neuroscience and Medicine-4,
Forschungszentrum Jülich, Jülich, Germany (E.F., A.M.O.P.,
N.J.S.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard
Medical School, Boston, Mass (D.C.A.); and Physical Measurement Laboratory,
National Institute of Standards and Technology, Boulder, Colo (K.E.K.)
| | - Ezequiel Farrher
- From the Department of Radiology, Boston University, 670 Albany St,
Boston, Mass 02118 (H.J., O.S.); Institute of Neuroscience and Medicine-4,
Forschungszentrum Jülich, Jülich, Germany (E.F., A.M.O.P.,
N.J.S.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard
Medical School, Boston, Mass (D.C.A.); and Physical Measurement Laboratory,
National Institute of Standards and Technology, Boulder, Colo (K.E.K.)
| | - Ana-Maria Oros-Peusquens
- From the Department of Radiology, Boston University, 670 Albany St,
Boston, Mass 02118 (H.J., O.S.); Institute of Neuroscience and Medicine-4,
Forschungszentrum Jülich, Jülich, Germany (E.F., A.M.O.P.,
N.J.S.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard
Medical School, Boston, Mass (D.C.A.); and Physical Measurement Laboratory,
National Institute of Standards and Technology, Boulder, Colo (K.E.K.)
| | - N. Jon Shah
- From the Department of Radiology, Boston University, 670 Albany St,
Boston, Mass 02118 (H.J., O.S.); Institute of Neuroscience and Medicine-4,
Forschungszentrum Jülich, Jülich, Germany (E.F., A.M.O.P.,
N.J.S.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard
Medical School, Boston, Mass (D.C.A.); and Physical Measurement Laboratory,
National Institute of Standards and Technology, Boulder, Colo (K.E.K.)
| | - David C. Alsop
- From the Department of Radiology, Boston University, 670 Albany St,
Boston, Mass 02118 (H.J., O.S.); Institute of Neuroscience and Medicine-4,
Forschungszentrum Jülich, Jülich, Germany (E.F., A.M.O.P.,
N.J.S.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard
Medical School, Boston, Mass (D.C.A.); and Physical Measurement Laboratory,
National Institute of Standards and Technology, Boulder, Colo (K.E.K.)
| | - Kathryn E. Keenan
- From the Department of Radiology, Boston University, 670 Albany St,
Boston, Mass 02118 (H.J., O.S.); Institute of Neuroscience and Medicine-4,
Forschungszentrum Jülich, Jülich, Germany (E.F., A.M.O.P.,
N.J.S.); Department of Radiology, Beth Israel Deaconess Medical Center, Harvard
Medical School, Boston, Mass (D.C.A.); and Physical Measurement Laboratory,
National Institute of Standards and Technology, Boulder, Colo (K.E.K.)
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Kirby ED, Frizzell TO, Grajauskas LA, Song X, Gawryluk JR, Lakhani B, Boyd L, D'Arcy RCN. Increased myelination plays a central role in white matter neuroplasticity. Neuroimage 2022; 263:119644. [PMID: 36170952 DOI: 10.1016/j.neuroimage.2022.119644] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 09/16/2022] [Accepted: 09/20/2022] [Indexed: 11/19/2022] Open
Abstract
White matter (WM) neuroplasticity in the human brain has been tracked non-invasively using advanced magnetic resonance imaging techniques, with increasing evidence for improved axonal transmission efficiency as a central mechanism. The current study is the culmination of a series of studies, which characterized the structure-function relationship of WM transmission efficiency in the cortico-spinal tract (CST) during motor learning. Here, we test the hypothesis that increased transmission efficiency is linked directly to increased myelination using myelin water imaging (MWI). MWI was used to evaluate neuroplasticity-related improvements in the CST. The MWI findings were then compared to diffusion tensor imaging (DTI) results, with the secondary hypothesis that radial diffusivity (RD) would have a stronger relationship than axial diffusivity (AD) if the changes were due to increased myelination. Both MWI and RD data showed the predicted pattern of significant results, strongly supporting that increased myelination plays a central role in WM neuroplasticity.
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Affiliation(s)
- Eric D Kirby
- BrainNET, Health and Technology District, Vancouver, Canada; Faculty of Individualized Interdisciplinary Studies, Simon Fraser University, Burnaby, Canada
| | - Tory O Frizzell
- BrainNET, Health and Technology District, Vancouver, Canada; Faculty of Applied Sciences, Simon Fraser University, Burnaby, Canada
| | - Lukas A Grajauskas
- Department of Biomedical, Physiology, and Kinesiology, Simon Fraser University, Burnaby, Canada; Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Xiaowei Song
- Department of Biomedical, Physiology, and Kinesiology, Simon Fraser University, Burnaby, Canada; Department of Research and Evaluation Services and Surrey Memorial Hospital, Fraser Health Authority, Surrey, Canada
| | - Jodie R Gawryluk
- Department of Psychology, University of Victoria, Victoria, Canada
| | - Bimal Lakhani
- BrainNET, Health and Technology District, Vancouver, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Lara Boyd
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Ryan C N D'Arcy
- BrainNET, Health and Technology District, Vancouver, Canada; Faculty of Applied Sciences, Simon Fraser University, Burnaby, Canada; Department of Research and Evaluation Services and Surrey Memorial Hospital, Fraser Health Authority, Surrey, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada.
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40
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Ma YJ, Jang H, Lombardi AF, Corey-Bloom J, Bydder GM. Myelin water imaging using a short-TR adiabatic inversion-recovery (STAIR) sequence. Magn Reson Med 2022; 88:1156-1169. [PMID: 35613378 PMCID: PMC9867567 DOI: 10.1002/mrm.29287] [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: 01/10/2022] [Revised: 03/21/2022] [Accepted: 04/13/2022] [Indexed: 01/26/2023]
Abstract
PURPOSE To develop a new myelin water imaging (MWI) technique using a short-TR adiabatic inversion-recovery (STAIR) sequence on a clinical 3T MR scanner. METHODS Myelin water (MW) in the brain has both a much shorter T1 and a much shorter T2 * than intracellular/extracellular water. A STAIR sequence with a short TR was designed to efficiently suppress long T1 signals from intracellular/extracellular water, and therefore allow selective imaging of MW, which has a much shorter T1 . Numerical simulation and phantom studies were performed to investigate the effectiveness of long T1 signal suppression. TheT2 * in white matter (WM) was measured with STAIR and compared with T2 * measured with a conventional gradient recall echo in in vivo study. Four healthy volunteers and 4 patients with multiple sclerosis were recruited for qualitative and quantitative MWI. Apparent MW fraction was generated to compare MW in normal WM in volunteers to MW in lesions in patients with multiple sclerosis. RESULTS Both simulation and phantom studies showed that when TR was sufficiently short (eg, 250 ms), the STAIR sequence effectively suppressed long T1 signals from tissues with a broad range of T1 s using a single TR/TI combination. The volunteer study showed a short T2 * of 9.5 ± 1.7 ms in WM, which is similar to reported values for MW. Lesions in patients with multiple sclerosis showed a significantly lower apparent MW fraction (4.5% ± 1.0%) compared with that of normal WM (9.2% ± 1.5%) in healthy volunteers (p < 0.05). CONCLUSIONS The STAIR sequence provides selective MWI in brain and can quantify reductions in MW content in patients with multiple sclerosis.
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Affiliation(s)
- Ya-Jun Ma
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Hyungseok Jang
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Alecio F. Lombardi
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Jody Corey-Bloom
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA
| | - Graeme M. Bydder
- Department of Radiology, University of California San Diego, San Diego, CA, USA
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41
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Filimonova E, Ovsiannikov K, Sosnov A, Perfilyev A, Gafurov R, Galaktionov D, Bervickiy A, Kiselev V, Rzaev J. Myelin damage and cortical atrophy in watershed regions in patients with moyamoya angiopathy. Front Neurosci 2022; 16:982829. [PMID: 36081657 PMCID: PMC9445365 DOI: 10.3389/fnins.2022.982829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 08/01/2022] [Indexed: 11/17/2022] Open
Abstract
Background Despite it being known that chronic ischemia results in myelin damage and gray matter atrophy, data regarding patients with moyamoya angiopathy is limited. We hypothesized that chronic ischemia in moyamoya angiopathy leads to myelin damage, especially in anterior watershed regions, as well as cortical atrophy in these areas. Materials and methods Twenty adult patients with moyamoya angiopathy and 17 age- and sex-matched healthy controls were evaluated using the T1w/T2w mapping method and surface-based MR-morphometry. The T1w/T2w signal intensity ratio, which reflects the white matter integrity, and the cortical thickness, were calculated in watershed regions and compared between the patients and controls. In the patients with moyamoya angiopathy, the correlations between these parameters and the Suzuki stage were also evaluated. Results The regional T1w/T2w ratio values from centrum semiovale in patients with MMA were significantly lower than those in healthy controls (p < 0.05); there was also a downward trend in T1w/T2w ratio values from middle frontal gyrus white matter in patients compared with the controls (p < 0.1). The cortical thickness of the middle frontal gyrus was significantly lower in patients than in healthy controls (p < 0.05). There were negative correlations between the Suzuki stage and the T1w/T2w ratio values from the centrum semiovale and middle frontal white matter. Conclusion T1w/T2w mapping revealed that myelin damage exists in watershed regions in patients with moyamoya angiopathy, in association with cortical atrophy according to MR-morphometry. These changes were correlated with the disease stage.
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Affiliation(s)
- Elena Filimonova
- Federal Center of Neurosurgery, Novosibirsk, Russia
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
- *Correspondence: Elena Filimonova,
| | | | | | | | | | - Dmitriy Galaktionov
- Federal Center of Neurosurgery, Novosibirsk, Russia
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
| | - Anatoliy Bervickiy
- Federal Center of Neurosurgery, Novosibirsk, Russia
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
| | | | - Jamil Rzaev
- Federal Center of Neurosurgery, Novosibirsk, Russia
- Department of Neurosurgery, Novosibirsk State Medical University, Novosibirsk, Russia
- Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Novosibirsk, Russia
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42
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Casella C, Chamberland M, Laguna PL, Parker GD, Rosser AE, Coulthard E, Rickards H, Berry SC, Jones DK, Metzler‐Baddeley C. Mutation-related magnetization-transfer, not axon density, drives white matter differences in premanifest Huntington disease: Evidence from in vivo ultra-strong gradient MRI. Hum Brain Mapp 2022; 43:3439-3460. [PMID: 35396899 PMCID: PMC9248323 DOI: 10.1002/hbm.25859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 03/07/2022] [Accepted: 03/27/2022] [Indexed: 11/10/2022] Open
Abstract
White matter (WM) alterations have been observed in Huntington disease (HD) but their role in the disease-pathophysiology remains unknown. We assessed WM changes in premanifest HD by exploiting ultra-strong-gradient magnetic resonance imaging (MRI). This allowed to separately quantify magnetization transfer ratio (MTR) and hindered and restricted diffusion-weighted signal fractions, and assess how they drove WM microstructure differences between patients and controls. We used tractometry to investigate region-specific alterations across callosal segments with well-characterized early- and late-myelinating axon populations, while brain-wise differences were explored with tract-based cluster analysis (TBCA). Behavioral measures were included to explore disease-associated brain-function relationships. We detected lower MTR in patients' callosal rostrum (tractometry: p = .03; TBCA: p = .03), but higher MTR in their splenium (tractometry: p = .02). Importantly, patients' mutation-size and MTR were positively correlated (all p-values < .01), indicating that MTR alterations may directly result from the mutation. Further, MTR was higher in younger, but lower in older patients relative to controls (p = .003), suggesting that MTR increases are detrimental later in the disease. Finally, patients showed higher restricted diffusion signal fraction (FR) from the composite hindered and restricted model of diffusion (CHARMED) in the cortico-spinal tract (p = .03), which correlated positively with MTR in the posterior callosum (p = .033), potentially reflecting compensatory mechanisms. In summary, this first comprehensive, ultra-strong gradient MRI study in HD provides novel evidence of mutation-driven MTR alterations at the premanifest disease stage which may reflect neurodevelopmental changes in iron, myelin, or a combination of these.
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Affiliation(s)
- Chiara Casella
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
- Department of Perinatal Imaging and Health, School of Biomedical Engineering & Imaging SciencesKing's College London, St Thomas' HospitalLondonUK
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenThe Netherlands
| | - Pedro L. Laguna
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Greg D. Parker
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Anne E. Rosser
- Department of Neurology and Psychological MedicineHayden Ellis BuildingCardiffUK
- School of BiosciencesCardiff UniversityCardiffUK
| | | | - Hugh Rickards
- Birmingham and Solihull Mental Health NHS Foundation TrustBirminghamUK
- Institute of Clinical Sciences, College of Medical and Dental SciencesUniversity of BirminghamBirminghamUK
| | - Samuel C. Berry
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Claudia Metzler‐Baddeley
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
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Fischi-Gomez E, Girard G, Koch PJ, Yu T, Pizzolato M, Brügger J, Piredda GF, Hilbert T, Cadic-Melchior AG, Beanato E, Park CH, Morishita T, Wessel MJ, Schiavi S, Daducci A, Kober T, Canales-Rodríguez EJ, Hummel FC, Thiran JP. Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions. FRONTIERS IN RADIOLOGY 2022; 2:930666. [PMID: 37492668 PMCID: PMC10365099 DOI: 10.3389/fradi.2022.930666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 06/30/2022] [Indexed: 07/27/2023]
Abstract
Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acquired in a healthy population. This study focuses on multi-echo T2 relaxometry, a qMRI technique that probes the complex tissue microstructure by differentiating compartment-specific T2 relaxation times. However, estimation methods are still limited by their sensitivity to the underlying noise. Moreover, estimating the model's parameters is challenging because the resulting inverse problem is ill-posed, requiring advanced numerical regularization techniques. As a result, the estimates from distinct regularization strategies are different. In this work, we aimed to investigate the variability and reproducibility of different techniques for estimating the transverse relaxation time of the intra- and extra-cellular space (T2IE) in gray (GM) and white matter (WM) tissue in a clinical setting, using a multi-site, multi-session, and multi-run T2 relaxometry dataset. To this end, we evaluated three different techniques for estimating the T2 spectra (two regularized non-negative least squares methods and a machine learning approach). Two independent analyses were performed to study the effect of using raw and denoised data. For both the GM and WM regions, and the raw and denoised data, our results suggest that the principal source of variance is the inter-subject variability, showing a higher coefficient of variation (CoV) than those estimated for the inter-site, inter-session, and inter-run, respectively. For all reconstruction methods studied, the CoV ranged between 0.32 and 1.64%. Interestingly, the inter-session variability was close to the inter-scanner variability with no statistical differences, suggesting that T2IE is a robust parameter that could be employed in multi-site neuroimaging studies. Furthermore, the three tested methods showed consistent results and similar intra-class correlation (ICC), with values superior to 0.7 for most regions. Results from raw data were slightly more reproducible than those from denoised data. The regularized non-negative least squares method based on the L-curve technique produced the best results, with ICC values ranging from 0.72 to 0.92.
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Affiliation(s)
- Elda Fischi-Gomez
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Translational Machine Learning Lab, Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Gabriel Girard
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Philipp J. Koch
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Department of Neurology, University of Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck, Lübeck, Germany
| | - Thomas Yu
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Marco Pizzolato
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Julia Brügger
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Gian Franco Piredda
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Tom Hilbert
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Andéol G. Cadic-Melchior
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Elena Beanato
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Chang-Hyun Park
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Takuya Morishita
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Maximilian J. Wessel
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Simona Schiavi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Alessandro Daducci
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Tobias Kober
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Erick J. Canales-Rodríguez
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Friedhelm C. Hummel
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Clinical Neuroscience, University Hospital of Geneva (HUG), Geneva, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
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Balasubramanian M, Mulkern RV, Polimeni JR. In vivo irreversible and reversible transverse relaxation rates in human cerebral cortex via line scans at 7 T with 250 micron resolution perpendicular to the cortical surface. Magn Reson Imaging 2022; 90:44-52. [PMID: 35398027 PMCID: PMC9930184 DOI: 10.1016/j.mri.2022.04.001] [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: 12/07/2021] [Revised: 03/10/2022] [Accepted: 04/02/2022] [Indexed: 01/15/2023]
Abstract
Understanding how and why MR signals and their associated relaxation rates vary with cortical depth could ultimately enable the noninvasive investigation of the laminar architecture of cerebral cortex in the living human brain. However, cortical gray matter is typically only a few millimeters thick, making it challenging to sample many cortical depths with the voxel sizes commonly used in MRI studies. Line-scan techniques provide a way to overcome this challenge and here we implemented a novel line-scan GESSE pulse sequence that allowed us to measure irreversible and reversible transverse relaxation rates-R2 and R2´, respectively-with extremely high resolution (250 μm) in the radial direction, perpendicular to the cortical surface. Eight healthy human subjects were scanned at 7 T using this sequence, with primary visual cortex (V1) targeted in three subjects and primary motor (M1) and somatosensory cortex (S1) targeted in the other five. In all three cortical areas, a peak in R2 values near the central depths was seen consistently across subjects-an observation that has not been made before, to our knowledge. On the other hand, no consistent pattern was apparent for R2´ values as a function of cortical depth. The intracortical R2 peak reported here is unlikely to be explained by myelin content or by deoxyhemoglobin in the microvasculature; however, this peak is in accord with the laminar distribution of non-heme iron in these cortical areas, known from prior histology studies. Obtaining information about tissue microstructure via measurements of transverse relaxation (and other quantitative MR contrast mechanisms) at the extremely high radial resolutions achievable through the use of line-scan techniques could therefore bring us closer to being able to perform "in vivo histology" of the cerebral cortex.
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Affiliation(s)
- Mukund Balasubramanian
- Harvard Medical School, Boston, MA, USA; Department of Radiology, Boston Children's Hospital, Boston, MA, USA.
| | - Robert V. Mulkern
- Harvard Medical School, Boston, MA, USA,Department of Radiology, Boston Children’s Hospital, Boston, MA, USA
| | - Jonathan R. Polimeni
- Harvard Medical School, Boston, MA, USA,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA,Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
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45
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Silva NCBS, Dao E, Hsu CL, Tam RC, Stein R, Alkeridy W, Laule C, Vavasour IM, Liu-Ambrose T. Myelin Content and Gait Impairment in Older Adults with Cerebral Small Vessel Disease and Mild Cognitive Impairment. Neurobiol Aging 2022; 119:56-66. [DOI: 10.1016/j.neurobiolaging.2022.03.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 02/19/2022] [Accepted: 03/15/2022] [Indexed: 11/25/2022]
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46
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Ferris JK, Greeley B, Vavasour IM, Kraeutner SN, Rinat S, Ramirez J, Black SE, Boyd LA. In vivo myelin imaging and tissue microstructure in white matter hyperintensities and perilesional white matter. Brain Commun 2022; 4:fcac142. [PMID: 35694147 PMCID: PMC9178967 DOI: 10.1093/braincomms/fcac142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 03/28/2022] [Accepted: 05/26/2022] [Indexed: 11/12/2022] Open
Abstract
White matter hyperintensities negatively impact white matter structure and relate to cognitive decline in aging. Diffusion tensor imaging detects changes to white matter microstructure, both within the white matter hyperintensity and extending into surrounding (perilesional) normal-appearing white matter. However, diffusion tensor imaging markers are not specific to tissue components, complicating the interpretation of previous microstructural findings. Myelin water imaging is a novel imaging technique that provides specific markers of myelin content (myelin water fraction) and interstitial fluid (geometric mean T2). Here we combined diffusion tensor imaging and myelin water imaging to examine tissue characteristics in white matter hyperintensities and perilesional white matter in 80 individuals (47 older adults and 33 individuals with chronic stroke). To measure perilesional normal-appearing white matter, white matter hyperintensity masks were dilated in 2 mm segments up to 10 mm in distance from the white matter hyperintensity. Fractional anisotropy, mean diffusivity, myelin water fraction, and geometric mean T2 were extracted from white matter hyperintensities and perilesional white matter. We observed a spatial gradient of higher mean diffusivity and geometric mean T2, and lower fractional anisotropy, in the white matter hyperintensity and perilesional white matter. In the chronic stroke group, myelin water fraction was reduced in the white matter hyperintensity but did not show a spatial gradient in perilesional white matter. Across the entire sample, white matter metrics within the white matter hyperintensity related to whole-brain white matter hyperintensity volume; with increasing white matter hyperintensity volume there was increased mean diffusivity and geometric mean T2, and decreased myelin water fraction in the white matter hyperintensity. Normal-appearing white matter adjacent to white matter hyperintensities exhibits characteristics of a transitional stage between healthy white matter and white matter hyperintensities. This effect was observed in markers sensitive to interstitial fluid, but not in myelin water fraction, the specific marker of myelin concentration. Within the white matter hyperintensity, interstitial fluid was higher and myelin concentration was lower in individuals with more severe cerebrovascular disease. Our data suggests white matter hyperintensities have penumbra-like effects in perilesional white matter that specifically reflect increased interstitial fluid, with no changes to myelin concentration. In contrast, within the white matter hyperintensity there are varying levels of demyelination, which vary based on the severity of cerebrovascular disease. Diffusion tensor imaging and myelin imaging may be useful clinical markers to predict white matter hyperintensity formation, and to stage neuronal damage within white matter hyperintensities.
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Affiliation(s)
- Jennifer K. Ferris
- University of British Columbia Graduate Programs in Rehabilitation Sciences, , Vancouver, Canada
| | - Brian Greeley
- University of British Columbia Department of Physical Therapy, , Vancouver, Canada
| | - Irene M. Vavasour
- The University of British Columbia Department of Radiology, , Vancouver, Canada
- University of British Columbia UBC MRI Research Centre, Faculty of Medicine, , Vancouver, Canada
| | - Sarah N. Kraeutner
- University of British Columbia Department of Psychology, , Okanagan, Kelowna, Canada
| | - Shie Rinat
- University of British Columbia Graduate Programs in Rehabilitation Sciences, , Vancouver, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Research Unit, Dr Sandra Black Centre for Brain Resilience and Recovery , Toronto, Canada
- Sunnybrook Research Institute, University of Toronto Hurvitz Brain Sciences Research Program, , Toronto, Canada
| | - Sandra E. Black
- LC Campbell Cognitive Neurology Research Unit, Dr Sandra Black Centre for Brain Resilience and Recovery , Toronto, Canada
- Sunnybrook Research Institute, University of Toronto Hurvitz Brain Sciences Research Program, , Toronto, Canada
| | - Lara A. Boyd
- University of British Columbia Graduate Programs in Rehabilitation Sciences, , Vancouver, Canada
- University of British Columbia Department of Physical Therapy, , Vancouver, Canada
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Brain imaging abnormalities in mixed Alzheimer's and subcortical vascular dementia. Neurol Sci 2022:1-14. [PMID: 35614521 DOI: 10.1017/cjn.2022.65] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Deoni SCL, O'Muircheartaigh J, Ljungberg E, Huentelman M, Williams SCR. Simultaneous high-resolution T 2 -weighted imaging and quantitative T 2 mapping at low magnetic field strengths using a multiple TE and multi-orientation acquisition approach. Magn Reson Med 2022; 88:1273-1281. [PMID: 35553454 PMCID: PMC9322579 DOI: 10.1002/mrm.29273] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 03/30/2022] [Accepted: 03/31/2022] [Indexed: 12/20/2022]
Abstract
PURPOSE Low magnetic field systems provide an important opportunity to expand MRI to new and diverse clinical and research study populations. However, a fundamental limitation of low field strength systems is the reduced SNR compared to 1.5 or 3T, necessitating compromises in spatial resolution and imaging time. Most often, images are acquired with anisotropic voxels with low through-plane resolution, which provide acceptable image quality with reasonable scan times, but can impair visualization of subtle pathology. METHODS Here, we describe a super-resolution approach to reconstruct high-resolution isotropic T2 -weighted images from a series of low-resolution anisotropic images acquired in orthogonal orientations. Furthermore, acquiring each image with an incremented TE allows calculations of quantitative T2 images without time penalty. RESULTS Our approach is demonstrated via phantom and in vivo human brain imaging, with simultaneous 1.5 × 1.5 × 1.5 mm3 T2 -weighted and quantitative T2 maps acquired using a clinically feasible approach that combines three acquisition that require approximately 4-min each to collect. Calculated T2 values agree with reference multiple TE measures with intraclass correlation values of 0.96 and 0.85 in phantom and in vivo measures, respectively, in line with previously reported brain T2 values at 150 mT, 1.5T, and 3T. CONCLUSION Our multi-orientation and multi-TE approach is a time-efficient method for high-resolution T2 -weighted images for anatomical visualization with simultaneous quantitative T2 imaging for increased sensitivity to tissue microstructure and chemical composition.
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Affiliation(s)
- Sean C L Deoni
- Advanced Baby Imaging Lab, Rhode Island Hospital, Providence, Rhode Island, USA.,Department of Diagnostic Radiology, Warren Alpert Medical School at Brown University, Providence, Rhode Island, USA.,Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, Rhode Island, USA
| | - Jonathan O'Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, Kings College London, London, UK.,Department of Perinatal Imaging and Health, Kings College London, London, UK.,MRC Centre for Neurodevelopmental Disorders, Kings College London, London, UK
| | - Emil Ljungberg
- Department of Medical Radiation Physics, Lund University, Lund, Sweden.,Department of Neuroimaging, Kings College London, London, UK
| | - Mathew Huentelman
- Neurogenomics Division, Translational Genomics Research Institute, Phoenix, Arizona, USA
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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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50
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Economou M, Billiet T, Wouters J, Ghesquière P, Vanderauwera J, Vandermosten M. Myelin water fraction in relation to fractional anisotropy and reading in 10-year-old children. Brain Struct Funct 2022; 227:2209-2217. [PMID: 35403895 DOI: 10.1007/s00429-022-02486-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 03/24/2022] [Indexed: 11/26/2022]
Abstract
Diffusion-weighted imaging studies have repeatedly shown that white matter correlates with reading throughout development. However, the neurobiological interpretation of this relationship is constrained by the limited microstructural specificity of diffusion imaging. A critical component of white matter microstructure is myelin, which can be investigated noninvasively using MRI. Here, we examined the link between myelin water fraction (MWF) and reading ability in 10-year-old children (n = 69). To better understand this relationship, we additionally investigated how these two variables relate to fractional anisotropy (FA; a common index of diffusion-weighted imaging). Our analysis revealed that lower MWF coheres with better reading scores in left-hemispheric tracts relevant for reading. While we replicated previous reports on a positive relationship between FA and MWF, we did not find any evidence for an association between reading and FA. Together, these findings contrast previous research suggesting that poor reading abilities might be rooted in lower myelination and emphasize the need for further longitudinal research to understand how this relationship evolves throughout reading development. Altogether, this study contributes important insights into the role of myelin-related processes in the relationship between reading and white matter structure.
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Affiliation(s)
- Maria Economou
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium.
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium.
- Leuven Brain Institute, KU Leuven, Leuven, Belgium.
| | - Thibo Billiet
- Icometrix, Research and Development, Leuven, Belgium
| | - Jan Wouters
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium
| | - Pol Ghesquière
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium
| | - Jolijn Vanderauwera
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, 3000, Leuven, Belgium
- Psychological Sciences Research Institute, Université Catholique de Louvain, 1348, Louvain-la-Neuve, Belgium
- Institute of Neuroscience, Université Catholique de Louvain, 1348, Louvain-la-Neuve, Belgium
| | - Maaike Vandermosten
- Research Group ExpORL, Department of Neurosciences, KU Leuven, 3000, Leuven, Belgium
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
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