Cited by 188Advanced Neuroimaging Techniques and ApplicationsMultiple Sclerosis Research StudiesAdvanced MRI Techniques and Applications

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In vivo quantification of demyelination and recovery using compartment-specific diffusion MRI metrics validated by electron microscopy

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Jelescu, Ileana O., Zurek, Magdalena, Winters, Kerryanne V., Veraart, Jelle, Rajaratnam, Anjali, Kim, Nathanael S., Babb, James S., Shepherd, Timothy M., Novikov, Dmitry S., Kim, Sungheon G., Fieremans, Els·2016·NeuroImage

DOI 10.1016/j.neuroimage.2016.02.004PMC PMC4851889

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Abstract

There is a need for accurate quantitative non-invasive biomarkers to monitor myelin pathology in vivo and distinguish myelin changes from other pathological features including inflammation and axonal loss. Conventional MRI metrics such as T2, magnetization transfer ratio and radial diffusivity have proven sensitivity but not specificity. In highly coherent white matter bundles, compartment-specific white matter tract integrity (WMTI) metrics can be directly derived from the diffusion and kurtosis tensors: axonal water fraction, intra-axonal diffusivity, and extra-axonal radial and axial diffusivities. We evaluate the potential of WMTI to quantify demyelination by monitoring the effects of both acute (6weeks) and chronic (12weeks) cuprizone intoxication and subsequent recovery in the mouse corpus callosum, and compare its performance with that of conventional metrics (T2, magnetization transfer, and DTI parameters). The changes observed in vivo correlated with those obtained from quantitative electron microscopy image analysis. A 6-week intoxication produced a significant decrease in axonal water fraction (p<0.001), with only mild changes in extra-axonal radial diffusivity, consistent with patchy demyelination, while a 12-week intoxication caused a more marked decrease in extra-axonal radial diffusivity (p=0.0135), consistent with more severe demyelination and clearance of the extra-axonal space. Results thus revealed increased specificity of the axonal water fraction and extra-axonal radial diffusivity parameters to different degrees and patterns of demyelination. The specificities of these parameters were corroborated by their respective correlations with microstructural features: the axonal water fraction correlated significantly with the electron microscopy derived total axonal water fraction (ρ=0.66; p=0.0014) but not with the g-ratio, while the extra-axonal radial diffusivity correlated with the g-ratio (ρ=0.48; p=0.0342) but not with the electron microscopy derived axonal water fraction. These parameters represent promising candidates as clinically feasible biomarkers of demyelination and remyelination in the white matter.

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Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
Elastix: a toolbox for intensity-based medical image registration
Klein, S., Staring, M., Murphy, K., Viergever, M. A., & Pluim, J. (2010) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2009.2035616 · Cited by 4,311
Diffusional kurtosis imaging: the quantification of non‐gaussian water diffusion by means of magnetic resonance imaging
Jensen, J. H., Helpern, J. A., Ramani, A., Lu, H., & Kaczynski, K. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20508 · Cited by 2,488
Demyelination increases radial diffusivity in corpus callosum of mouse brain
Song, S.-K., Yoshino, J., Le, T. Q., Lin, S.-J., Sun, S.-W., Cross, A. H., & Armstrong, R. C. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.01.028 · Cited by 1,658
The Mouse in Biomedical Research
(1983) · Elsevier eBooks · doi:10.1016/c2013-0-10677-0 · Cited by 1,021
A white matter disorder in dementia of the Alzheimer type: A pathoanatomical study
Brun, A., & Englund, E. (1986) · Annals of Neurology · doi:10.1002/ana.410190306 · Cited by 1,014
The Neurotoxicant, Cuprizone, as a Model to Study Demyelination and Remyelination in the Central Nervous System
Matsushima, G. K., & Morell, P. (2001) · Brain Pathology · doi:10.1111/j.1750-3639.2001.tb00385.x · Cited by 984
CellProfiler™: Free, Versatile Software for Automated Biological Image Analysis
Lamprecht, M. R., Sabatini, D. M., & Carpenter, A. E. (2007) · BioTechniques · doi:10.2144/000112257 · Cited by 880

Flagged first, then by citations

Show all 55 references

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Fieremans, 2012, Diffusion distinguishes between axonal loss and demyelination in brain white matter, Proc. Intl. Soc. Magn. Reson. Med., 20
Novikov, 2012, Relating extracellular diffusivity to cell size distribution and packing density as applied to white matter, Proc. Intl. Soc. Mag. Reson. Med., 20, 1829
Novikov, 2015, From diffusion signal moments to neurite diffusivities, volume fraction and orientation distribution: an exact solution, Proc. Intl. Soc. Mag. Reson. Med., 23, 469

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Authors: Jelescu, I. O., Zurek, M., Winters, K. V., Veraart, J., Rajaratnam, A., Kim, N. S., Babb, J. S., Shepherd, T. M., Novikov, D. S., Kim, S. G., & Fieremans, E.
Affiliations: NYU Langone Health (US)
New York University (US)
Corresponding author: Jelescu, Ileana O.
ORCID: Jelescu, Ileana O.
Zurek, Magdalena
Veraart, Jelle
Babb, James S.
Shepherd, Timothy M.
Novikov, Dmitry S.
Kim, Sungheon G.
Fieremans, Els
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2016-05
Volume: 132
Pages: 104-114
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2016.02.004
PMC: PMC4851889
OpenAlex: W2269202100
Cited by: 188
References: 55
Citations by year: 2026: 12 · 2025: 19 · 2024: 23 · 2023: 11 · 2022: 14 · 2021: 22 · 2020: 21 · 2019: 17 · 2018: 19 · 2017: 20 · 2016: 10
FWCI: 19.10
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: NINDS (R21 NS081230, R01 NS088040)
NCATS (UL1 TR00038)
Raymond and Beverly Sackler Laboratories for the Convergence of Biomedical, Physical, and Engineering Sciences
Center of Advanced Imaging Innovation and Research (P41 EB017183)
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Health Sciences › Medicine › Clinical Neurology › Multiple Sclerosis Research Studies
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Keywords: demyelination, remyelination, white matter tract integrity, corpus callosum, g-ratio, white matter microstructure
MeSH terms: Remyelination, Animals, Brain Mapping, Corpus Callosum, Cuprizone, Demyelinating Diseases, Diffusion, Female, Mice, Inbred C57BL, Microscopy, Electron, Myelin Sheath, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging

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In vivo quantification of demyelination and recovery using compartment-specific diffusion MRI metrics validated by electron microscopy

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