Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain

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

doi:10.1002/ana.20202

Cited by 693 publications

(715 citation statements)

References 53 publications

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“…21 Although subject to short-term fluctuations similar to lesion contrast, MT has been strongly associated with demyelination and axonal loss in histology. 22,23 MT is therefore expected to be more sensitive to the destructive aspects of disease activity, supporting the concept of subacute disease that reaches neither a clinical threshold nor becomes visible as focal MRI changes.…”

Section: Mri Variablesmentioning

confidence: 87%

Time-Series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential?

Meier

Weiner

2007

Neurotherapeutics

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Summary:This article discusses and reviews advanced forms of serial morphometry in the context of a disease progression model in multiple sclerosis (MS). This model of disease activity distinguishes between overall disease activity and the proportion thereof that becomes permanent damage. This translates into a progression model that features a repair potential, which, when exhausted, marks the conversion or progression from relapsing to progressive disease. The level of repair capacity at a given time determines the rate of progression. Both clinical and MRI variables appear to be in support of such a model. We examine possible MRI markers for this repair capacity, particularly the short-term behavior of new MRI lesions, quantified by methods of time-series analysis-that is, capturing lesion dynamics in the form of MRI intensity change directly, rather than shape or volume change. Lower rates of individual lesion recovery may represent lower repair and greater proximity to a progressive stage. Individuals with low transient lesion turnover appear to undergo more rapid progression and atrophy. Because disease-modifying therapies aim to alter the pathophysiological chain of inflammation, demyelination, and axonal loss, a therapeutic effect may therefore be more readily apparent as a change in lesion dynamics and recovery rate and level, rather than a change in total lesion burden or enhancing lesion number. Key Words: Multiple sclerosis, disease modeling, serial MRI, morphometry, lesion evolution, repair. THE REPAIR POTENTIAL HYPOTHESISMore than 80% of newly diagnosed cases of clinically definite multiple sclerosis (MS) fall into the relapsingremitting (RRMS) category. A large proportion of RRMS patients eventually convert to a secondary progressive stage (SPMS) within 6 -10 years. 1,2 The hallmark of this stage is a progressive worsening of disability in the absence of relapses, and a shift from inflammatory to degenerative activity, apparent on MRI as fewer contrast-enhancing lesions and accelerated brain parenchymal atrophy (FIG. 1). The etiology of this progression is not known, but a premise commonly offered is that of a threshold effect and the exhaustion of structural and functional redundancy, leading from inflammatory and relapsing to more diffuse and accelerated accrual of damage.Here we review and discuss this progression model, focusing on the concept of a hypothesized repair potential as a marker for progression. Of particular interest is the possibility of obtaining early MRI markers of this repair potential from advanced forms of serial quantitativ MRI. As new therapies with alternative mechanisms (other than broad or targeted immune suppression) become available to MS patients, specific markers that reliably predict long-term progression early in the disease are becoming increasingly critical.A growing body of evidence is congruent with a repair potential model: histopathological analyses have revealed a shift from focal inflammatory activity in RRMS to diffuse damage in SPMS 3 and overall reduced...

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Section: Mri Variablesmentioning

confidence: 87%

Time-Series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential?

Meier

Weiner

2007

Neurotherapeutics

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“…Multiple sclerosis is a central nervous system disease characterized by a complex pathophysiology,1 the fundamental features of which have been derived from the analysis of post mortem tissue 2, 3, 4, 5. Spinal cord pathology is an important determinant of permanent neurological disability with cardinal characteristics being inflammatory demyelination, synaptic, neuronal and axonal loss 6, 7, 8, 9, 10, 11.…”

Section: Introductionmentioning

confidence: 99%

Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

Grussu

Schneider

Tur

et al. 2017

Ann Clin Transl Neurol

265

243

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ObjectiveConventional magnetic resonance imaging (MRI) of the multiple sclerosis spinal cord is limited by low specificity regarding the underlying pathological processes, and new MRI metrics assessing microscopic damage are required. We aim to show for the first time that neurite orientation dispersion (i.e., variability in axon/dendrite orientations) is a new biomarker that uncovers previously undetected layers of complexity of multiple sclerosis spinal cord pathology. Also, we validate against histology a clinically viable MRI technique for dispersion measurement (neurite orientation dispersion and density imaging, NODDI), to demonstrate the strong potential of the new marker.MethodsWe related quantitative metrics from histology and MRI in four post mortem spinal cord specimens (two controls; two progressive multiple sclerosis cases). The samples were scanned at high field, obtaining maps of neurite density and orientation dispersion from NODDI and routine diffusion tensor imaging (DTI) indices. Histological procedures provided markers of astrocyte, microglia, myelin and neurofilament density, as well as neurite dispersion.ResultsWe report from both NODDI and histology a trend toward lower neurite dispersion in demyelinated lesions, indicative of reduced neurite architecture complexity. Also, we provide unequivocal evidence that NODDI‐derived dispersion matches its histological counterpart (P < 0.001), while DTI metrics are less specific and influenced by several biophysical substrates.InterpretationNeurite orientation dispersion detects a previously undescribed and potentially relevant layer of microstructural complexity of multiple sclerosis spinal cord pathology. Clinically feasible techniques such as NODDI may play a key role in clinical trial and practice settings, as they provide histologically meaningful dispersion indices.

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“…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

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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...

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Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain

Cited by 693 publications

References 53 publications

Time-Series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential?

Time-Series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential?

Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

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

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Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain

Cited by 693 publications

References 53 publications

Time-Series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential?

Time-Series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential?

Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

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

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Product

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