Quantitative analysis of the myelin g -ratio from electron microscopy images of the macaque corpus callosum

Stikov, Nikola; Campbell, Jennifer S. W.; Stroh, Thomas; Lavelée, Mariette; Frey, Stephen; Novek, Jennifer; Nuara, Stephen G.; Ho, Ming-Kai; Bedell, Barry J.; Dougherty, Robert F.; Leppert, Ilana R.; Boudreau, Mathieu; Narayanan, Sridar; Duval, Tanguy; Cohen‐Adad, Julien; Picard, Paul-Alexandre; Gąsecka, Alicja; Côté, Daniel; Pike, G. Bruce

doi:10.1016/j.dib.2015.05.019

Cited by 49 publications

(68 citation statements)

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“…Neurons can be subdivided into fibers, cell bodies and dendrites. In the white matter, we observe very few neuronal bodies and dendrites 1 , and the majority of the space is occupied by neuronal fibers (~60%) (Mottershead et al, 2003;Perge et al, 2009;Stikov et al, 2015a). The extracellular space constitutes about 20% of the volume (Bourne, 2012;Syková and Nicholson, 2008), blood vessels constitute less than 3% (Syková and Nicholson, 2008), while the rest of the volume is occupied by glial cells.…”

Section: White Matter Microstructurementioning

confidence: 99%

“…While the white matter appears homogeneous on conventional MRI scans, quantitative MRI reveals microstructural differences, notably between different regions of the corpus callosum (Alexander et al, 2010;Barazany et al, 2009;Mezer et al, 2013;Stikov et al, 2015a) or between spinal cord tracts (Duval et al, 2015;Duval et al, 2016a;Fujiyoshi et al, 2016;. These metrics can also track the microstructural changes related to brain development (Dean et al, 2016;MacMillan et al, 2011;Saito et al, 2012) or tissue deterioration in pathology (Chong et al, 2016;Fujiyoshi et al, 2016;Klawiter et al, 2011;Schmierer et al, 2008;Stikov et al, 2015a).…”

Section: Sensitivitymentioning

confidence: 99%

“…While the lack of specificity of the early quantitative MRI metrics is commonly pointed out (Alexander et al, 2007;Schwartz et al, 2005;Wheeler-Kingshott and Cercignani, 2009), model-based metrics bring new information (i.e. not perfectly correlated with conventional metrics) (Alexander et al, 2010;Zhang et al, 2012) that correlates with histology (Alexander et al, 2010;Barazany et al, 2009;Dula et al, 2010;Duval et al, 2015Duval et al, , 2016bOng and Wehrli, 2010;West et al, 2016b), and improves specificity in lesions (Kipp et al, 2016;Stikov et al, 2015a). More comprehensive models (Burcaw et al, 2015), as well as a new paradigm for measuring myelin (Sheth et al, 2016), should further improve the specificity of these metrics.…”

Section: Specificitymentioning

confidence: 99%

“…The myelin sheath is thus a succession of impermeable bilipid layers, separated by layers of water (myelin water). In adults, the myelin sheath occupies approximately 25-30% of the white matter volume (Mottershead et al, 2003;Perge et al, 2009;Stikov et al, 2015a). The function of the myelin layers is to improve the speed of propagation of action potentials by inhibiting ionic exchanges between the intra-and the extra-axonal space.…”

Section: White Matter Microstructurementioning

confidence: 99%

“…Myelin volume fraction (MVF) was obtained using a qMT (Henkelman et al, 1993), axon volume fraction (AVF) was computed using the NOD-DI model (Zhang et al, 2012), and g-ratio was calculated from AVF and MVF (Stikov et al, 2015a). Conventional FLAIR contrast indicates the presence of three hyperintense lesions.…”

Section: Modeling White Matter Microstructurementioning

confidence: 99%

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Modeling white matter microstructure

Duval¹,

Stikov²,

Cohen‐Adad³

2016

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SummaryQuantitative magnetic resonance imaging can be combined with advanced biophysical models to measure microstructural features of white matter. Non-invasive microstructural imaging has the potential to revolutionize neuroscience, and acquiring these measures in clinically feasible times would greatly improve patient monitoring and clinical studies of drug efficacy. However, a good understanding of microstructural imaging techniques is essential to set realistic expectations and to prevent over-interpretation of results. This review explains the methodology behind microstructural modeling and imaging, and gives an overview of the breakthroughs and challenges associated with it.

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Section: White Matter Microstructurementioning

confidence: 99%

Section: Sensitivitymentioning

confidence: 99%

Section: Specificitymentioning

confidence: 99%

Section: White Matter Microstructurementioning

confidence: 99%

Section: Modeling White Matter Microstructurementioning

confidence: 99%

See 3 more Smart Citations

Modeling white matter microstructure

Duval¹,

Stikov²,

Cohen‐Adad³

2016

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Ultrastructural Axon–Myelin Unit Alterations in Multiple Sclerosis Correlate with Inflammation

Bosch

Hümmert²,

Steyer³

et al. 2023

Annals of Neurology

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Objective: Changes in the normal-appearing white matter (NAWM) in multiple sclerosis (MS) may contribute to disease progression. Here, we systematically quantified ultrastructural and subcellular characteristics of the axon-myelin unit in MS NAWM and determined how this correlates with low-grade inflammation. Methods: Human brain tissue obtained with short postmortem delay and fixation at autopsy enables systematic quantification of ultrastructural characteristics. In this study, we performed high-resolution immunohis tochemistry and quantitative transmission electron microscopy to study inflammation and ultrastructural characteristics of the axon-myelin unit in MS NAWM (n = 8) and control white matter (WM) in the optic nerve. Results: In the MS NAWM, there were more activated and phagocytic microglia cells (HLA + P2RY12 À and Iba1 + CD68 + ) and more T cells (CD3 + ) compared to control WM, mainly located in the perivascular space. In MS NAWM compared to control WM, there were, as expected, longer paranodes and juxtaparanodes and larger overlap between paranodes and juxtaparanodes. There was less compact myelin wrapping, a lower g-ratio, and a higher frequency of axonal mitochondria. Changes in myelin and axonal mitochondrial frequency correlated positively with the number of active and phagocytic microglia and lymphocytes in the optic nerve. Interpretation: These data suggest that in MS NAWM myelin detachment and uncompact myelin wrapping occurs, potassium channels are unmasked at the nodes of Ranvier, and axonal energy demand is increased, or mitochondrial transport is stagnated, accompanied by increased presence of activated and phagocytic microglia and T cells. These subclinical alterations to the axon-myelin unit in MS NAWM may contribute to disease progression.

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Ultrahigh field imaging of myelin disease models: Toward specific markers of myelin integrity?

Petiet

Adanyeguh

Aigrot

et al. 2019

J of Comparative Neurology

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Specific magnetic resonance imaging (MRI) markers of myelin are critical for the evaluation and development of regenerative therapies for demyelinating diseases. Several MRI methods have been developed for myelin imaging, based either on acquisition schemes or on mathematical modeling of the signal. They generally showed good sensitivity but validation for specificity toward myelin is still warranted to allow a reliable interpretation in an in vivo complex pathological environment. Experimental models of dys−/demyelination are characterized by various levels of myelin disorders, axonal damage, gliosis and inflammation, and offer the opportunity for powerful correlative studies between imaging metrics and histology. Here, we review how ultrahigh field MRI markers have been correlated with histology in these models and provide insights into the trends for future developments of MRI tools in human myelin diseases. To this end, we present the biophysical basis of the main MRI methods for myelin imaging based on T 1 , T 2 , water diffusion, and magnetization transfer signal, the characteristics of animal models used and the outcomes of histological validations. To date such studies are limited, and demonstrate partial correlations with immunohistochemical and electron microscopy measures of myelin.These MRI metrics also often correlate with axons, glial, or inflammatory cells in models where axonal degeneration or inflammation occur as potential confounding factors. Therefore, the MRI markers' specificity for myelin is still perfectible and future developments should improve mathematical modeling of the MR signal based on more complex systems or provide multimodal approaches to better disentangle the biological processes underlying the MRI metrics. K E Y W O R D Shistological correlation, MRI markers, multiple sclerosis, myelin, specificity

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Quantitative analysis of the myelin g -ratio from electron microscopy images of the macaque corpus callosum

Cited by 49 publications

References 4 publications

Modeling white matter microstructure

Modeling white matter microstructure

Ultrastructural Axon–Myelin Unit Alterations in Multiple Sclerosis Correlate with Inflammation

Ultrahigh field imaging of myelin disease models: Toward specific markers of myelin integrity?

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