Quantitative magnetization transfer imaging in postmortem multiple sclerosis brain

Schmierer, Klaus; Tozer, Daniel J.; Salvatore, Francesco; Altmann, Daniel R.; Barker, Gareth J.; Tofts, PS; Miller, David H.

doi:10.1002/jmri.20984

Cited by 252 publications

(310 citation statements)

References 55 publications

Supporting

Mentioning

297

Contrasting

Order By: Relevance

“…They concluded that both techniques are sufficiently suited to detect microstructural tissue alterations at least in the white matter of the murine brain. Postmortem histological analyses assessing myelin content, axonal density, and gliosis revealed similar correlations in brains of patients with Alzheimer's disease [29] or multiple sclerosis [71][72][73].…”

Section: Age-related White Matter Changes and Normal-appearing Brain mentioning

confidence: 71%

“…As can also be seen from Table 4 in vivo studies in humans consistently reported that mean diffusivity and fractional anisotropy, and in most investigations also magnetization transfer ratios, are more affected in agerelated white matter lesions than in normal-appearing white matter [7,22,43,59,69,72,81]. There existed a significant association between white matter lesion load and severity of DTI and MTR measures in the normalappearing white matter with the microstructural changes in normal brain tissue being more closely related to the patients' clinical presentation than the volume of visible white matter abnormalities [9,32,52,61,69,70,74,92,93].…”

Section: Age-related White Matter Changes and Normal-appearing Brain mentioning

confidence: 73%

See 1 more Smart Citation

Heterogeneity in age-related white matter changes

et al. 2011

View full text Add to dashboard Cite

White matter changes occur endemically in routine magnetic resonance imaging (MRI) scans of elderly persons. MRI appearance and histopathological correlates of white matter changes are heterogeneous. Smooth periventricular hyperintensities, including caps around the ventricular horns, periventricular lining and halos are likely to be of non-vascular origin. They relate to a disruption of the ependymal lining with subependymal widening of the extracellular space and have to be differentiated from subcortical and deep white matter abnormalities. For the latter a distinction needs to be made between punctate, early confluent and confluent types. Although punctate white matter lesions often represent widened perivascular spaces without substantial ischemic tissue damage, early confluent and confluent lesions correspond to incomplete ischemic destruction. Punctate abnormalities on MRI show a low tendency for progression, while early confluent and confluent changes progress rapidly. The causative and modifying pathways involved in the occurrence of sporadic age-related white matter changes are still incompletely understood, but recent microarray and genome-wide association approaches increased the notion of pathways that might be considered as targets for therapeutic intervention. The majority of differentially regulated transcripts in white matter lesions encode genes associated with immune function, cell cycle, proteolysis, and ion transport. Genome-wide association studies identified six SNPs mapping to a locus on chromosome 17q25 to be related to white matter lesion load in the general population. We also report first and preliminary data that demonstrate apolipoprotein E (ApoE) immunoreactivity in white matter lesions and support epidemiological findings indicating that ApoE is another factor possibly related to white matter lesion occurrence. Further insights come from modern MRI techniques, such as diffusion tensor and magnetization transfer imaging, as they provide tools for the characterization of

show abstract

Section: Age-related White Matter Changes and Normal-appearing Brain mentioning

confidence: 71%

Section: Age-related White Matter Changes and Normal-appearing Brain mentioning

confidence: 73%

Heterogeneity in age-related white matter changes

et al. 2011

View full text Add to dashboard Cite

show abstract

“…PET ligands targeting the 18 kDa translocator protein, which is upregulated with inflammation, detect neuroinflammation in human diseases including multiple sclerosis and in animal models, but the effectiveness of these PET markers remains to be seen (Banati et al, 2000;Papadopoulos et al, 2006;Chauveau et al, 2009Chauveau et al, , 2011Abourbeh et al, 2012;Xie et al, 2012). Promising advances in imaging myelination have been reported including myelin water imaging (MacKay et al, 1994;Du et al, 2007;Laule et al, 2008;Hwang et al, 2010;Prasloski et al, 2012), magnetization transfer (Inglese et al, 2003;Schmierer et al, 2004Schmierer et al, , 2007aDortch et al, 2011;Stikov et al, 2011;Underhill et al, 2011), optical imaging (Wang et al, 2011a) and myelin-specific PET markers (Wang et al, 2009;Wu et al, 2013). For specifically identifying axon injury and loss, reduced NAA content measured by magnetic resonance spectroscopy (MRS) has been used (De Stefano et al, 1999;Aboul-Enein et al, 2010;Wood et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

“…Currently available quantitative MRI techniques have been validated using standard histology (Mottershead et al, 2003;Schmierer et al, 2003Schmierer et al, , 2004Schmierer et al, , 2007aFisniku et al, 2009). However, a rigorously quantitative validation of magnetic resonance pathologic metrics has been relatively limited in part due to the difficulty to co-register quantitative histology findings with MRI.…”

Section: Discussionmentioning

confidence: 99%

Differentiation and quantification of inflammation, demyelination and axon injury or loss in multiple sclerosis

Wang

Sun

Wang

et al. 2015

Brain

139

189

View full text Add to dashboard Cite

Axon injury/loss, demyelination and inflammation are the primary pathologies in multiple sclerosis lesions. Despite the prevailing notion that axon/neuron loss is the substrate of clinical progression of multiple sclerosis, the roles that these individual pathological processes play in multiple sclerosis progression remain to be defined. An imaging modality capable to effectively detect, differentiate and individually quantify axon injury/loss, demyelination and inflammation, would not only facilitate the understanding of the pathophysiology underlying multiple sclerosis progression, but also the assessment of treatments at the clinical trial and individual patient levels. In this report, the newly developed diffusion basis spectrum imaging was used to discriminate and quantify the underlying pathological components in multiple sclerosis white matter. Through the multiple-tensor modelling of diffusion weighted magnetic resonance imaging signals, diffusion basis spectrum imaging resolves inflammation-associated cellularity and vasogenic oedema in addition to accounting for partial volume effects resulting from cerebrospinal fluid contamination, and crossing fibres. Quantitative histological analysis of autopsied multiple sclerosis spinal cord specimens supported that diffusion basis spectrum imaging-determined cellularity, axon and myelin injury metrics closely correlated with those pathologies identified and quantified by conventional histological staining. We demonstrated in healthy control subjects that diffusion basis spectrum imaging rectified inaccurate assessments of diffusion properties of white matter tracts by diffusion tensor imaging in the presence of cerebrospinal fluid contamination and/or crossing fibres. In multiple sclerosis patients, we report that diffusion basis spectrum imaging quantitatively characterized the distinct pathologies underlying gadolinium-enhanced lesions, persistent black holes, non-enhanced lesions and non-black hole lesions, a task yet to be demonstrated by other neuroimaging approaches. Diffusion basis spectrum imaging-derived radial diffusivity (myelin integrity marker) and non-restricted isotropic diffusion fraction (oedema marker) correlated with magnetization transfer ratio, supporting previous reports that magnetization transfer ratio is sensitive not only to myelin integrity, but also to inflammation-associated oedema. Our results suggested that diffusion basis spectrum imaging-derived quantitative biomarkers are highly consistent with histology findings and hold promise to accurately characterize the heterogeneous white matter pathology in multiple sclerosis patients. Thus, diffusion basis spectrum imaging can potentially serve as a non-invasive outcome measure to assess treatment effects on the specific components of underlying pathology targeted by new multiple sclerosis therapies. Keywords: diffusion basis spectrum imaging; diffusion tensor imaging; white matter injury; inflammation; multiple sclerosis Abbreviations: DTI = diffusion tensor imaging; DBSI = diffusion...

show abstract

“…Separating the fundamental parameters of the two-pool model requires an additional measurement of the "long" observed T 1 (T 1obs ), from which the free pool R 1f can then be computed (6). The MWF, MT ratio, and certain QMTI parameters have respectively been shown to correlate with myelin content and demyelination (11)(12)(13).…”

mentioning

confidence: 99%

Characterizing healthy and diseased white matter using quantitative magnetization transfer and multicomponent T₂ relaxometry: A unified view via a four‐pool model

Levesque

Pike

2009

Magnetic Resonance in Med

View full text Add to dashboard Cite

Nuclear magnetic resonance relaxation and magnetization transfer in cerebral white matter can be described using a four-pool model: two for water protons (in separate myelin and intra/extracellular compartments) and two for protons associated with the lipids and proteins of biologic membranes (of myelin and nonmyelin semisolids). This model was used to gain insight into the observations from multicomponent quantitative T 2 relaxometry and quantitative magnetization transfer imaging, both based on simplified white matter models and experimentally feasible in vivo. The sensitivity of MRI to white matter (WM) damage in diseases such as multiple sclerosis (MS) has made it indispensable in diagnosis, but its lack of pathologic specificity remains problematic. In response, investigators have turned to quantitative MRI techniques to identify putative indicators of specific pathologic features, such as myelin loss. Quantitative analysis of spin-spin relaxation data using T 2 distributions (QT2), also known as myelin water imaging, can notably distinguish two major T 2 components in human WM (1,2). In particular, QT2 yields an estimate of the myelin water fraction (MWF), the fraction of water contained between the layers of myelin in WM. Magnetization transfer (MT) imaging (3,4), most often measured as the MT ratio, is a widely available technique that is sensitive to the semisolid constituents of tissue (e.g., lipids, proteins), and in WM the MT effect is believed to be dominated by myelin (5). The MT ratio is a semiquantitative index that presents a limited view of the MT effect. More detailed analysis of pulsed, off-resonance MT data using the two-pool model of tissue (6,7) has been extended to in vivo imaging, in particular in human WM (8-10). The resulting method, termed quantitative MT imaging (QMTI), allows mapping of the parameters of the two-pool (liquid and semisolid) model of tissue: the ratio of semisolid to liquid protons F, the first-order forward and reverse exchange rate constants k f and k r (where k r ϭ k f /F), the spin-lattice relaxation rate R 1f of the free pool (R 1f ϭ 1/T 1f ), the spin-spin relaxation time constant of the free pool T 2f , and the "T 2 " of the restricted pool, T 2r (inversely related to the width of the restricted pool resonance). Separating the fundamental parameters of the two-pool model requires an additional measurement of the "long" observed T 1 (T 1obs ), from which the free pool R 1f can then be computed (6). The MWF, MT ratio, and certain QMTI parameters have respectively been shown to correlate with myelin content and demyelination (11-13).QT2 and QMTI techniques each present a different limited view of WM characteristics. QT2 imaging relies on the fundamental assumptions that water exists in isolated compartments and that variations in the estimated MWF are equal to variations in myelin. On the other hand, the two-pool model for MT neglects the existence of multiple water pools. A more comprehensive model for WM that includes four communicating proton pools (myelin soli...

show abstract

Quantitative magnetization transfer imaging in postmortem multiple sclerosis brain

Cited by 252 publications

References 55 publications

Heterogeneity in age-related white matter changes

Heterogeneity in age-related white matter changes

Differentiation and quantification of inflammation, demyelination and axon injury or loss in multiple sclerosis

Characterizing healthy and diseased white matter using quantitative magnetization transfer and multicomponent T₂ relaxometry: A unified view via a four‐pool model

Contact Info

Product

Resources

About

Quantitative magnetization transfer imaging in postmortem multiple sclerosis brain

Cited by 252 publications

References 55 publications

Heterogeneity in age-related white matter changes

Heterogeneity in age-related white matter changes

Differentiation and quantification of inflammation, demyelination and axon injury or loss in multiple sclerosis

Characterizing healthy and diseased white matter using quantitative magnetization transfer and multicomponent T2 relaxometry: A unified view via a four‐pool model

Contact Info

Product

Resources

About

Characterizing healthy and diseased white matter using quantitative magnetization transfer and multicomponent T₂ relaxometry: A unified view via a four‐pool model