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Table of Contents    
NI FEATURE: THE EDITORIAL DEBATE III-- PROS AND CONS
Year : 2018  |  Volume : 66  |  Issue : 3  |  Page : 667-668

Relapsing-remitting multiple sclerosis: Blood-brain barrier permeability and intravascular leakage measurement by dynamic contrast-enhanced MRI and the extended Tofts linear model


Department of Medicine, Imperial College, London, UK

Date of Web Publication15-May-2018

Correspondence Address:
Dr. Basant K Puri
Imaging Directorate, Block A, Level 1, Hammersmith Hospital, Du Cane Road, London W12 0HS
UK
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0028-3886.232317

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How to cite this article:
Puri BK. Relapsing-remitting multiple sclerosis: Blood-brain barrier permeability and intravascular leakage measurement by dynamic contrast-enhanced MRI and the extended Tofts linear model. Neurol India 2018;66:667-8

How to cite this URL:
Puri BK. Relapsing-remitting multiple sclerosis: Blood-brain barrier permeability and intravascular leakage measurement by dynamic contrast-enhanced MRI and the extended Tofts linear model. Neurol India [serial online] 2018 [cited 2018 Aug 20];66:667-8. Available from: http://www.neurologyindia.com/text.asp?2018/66/3/667/232317




In their 1991 seminal paper on the use of dynamic magnetic resonance imaging for the measurement of blood-brain barrier permeability and the leakage space, Paul Tofts and Allan Kermode predicted that their technique is likely to be useful in the study of all conditions of the central nervous system in which the blood-brain barrier is disturbed, e.g., multiple sclerosis'.[1] Indeed, this technique was doubtless developed with multiple sclerosis (MS) in mind; both Tofts and Kermode were based at the Multiple Sclerosis NMR Research Group at Queen Square, London, at the time this work was carried out.

Their underlying model has two components. First, the time-course of the change in concentration of a gadolinium-based contrast agent is mathematically modelled. The conventional modelling by a bi-exponential decay second-order differential equation, in which loss of the contrast agent from the plasma compartment takes place via movement into the extracellular space and by renal loss, is extended to include leakage via the blood-brain barrier into a compartment termed the 'lesion leakage space' by Tofts and Kermode; the lesion here can be considered to be part of the blood-brain barrier which is not functioning correctly, and anatomically the corresponding leakage space might be a perivascular region around cerebral capillaries or an extracellular space in the lesion itself. The second component of the model relates to the linear relationship between the concentration of the gadolinium-based contrast agent and the reciprocals of MRI signal relaxation times pre- and post-injection of the contrast agent, which gives rise to spin-echo and inversion-recovery signal intensity equations. The latter can be solved, via a least-squares method, using values from a tri-exponential differential equation from the first component of the model. It should be noted that this work of Tofts and Kermode was partly based on modelling by Ian Young and colleagues.[2]

In spite of the prediction of Tofts and Kermode, there have been few applications of dynamic contrast-enhanced T1-weighted MRI to MS. In the present issue of Neurology India, Yin, Xiong, Liu, Sah, Zeng, Wang and Li, from The First Affiliated Hospital of Chongqing Medical University, China, have applied this technique, together with the extended Tofts model, to a cross-sectional neuroimaging study of 30 patients suffering from relapsing-remitting MS (RRMS).[3],[4] Significant differences were found between contrast-enhancing lesions and both non-enhancing lesions and normal-appearing white matter in respect of a number of MRI parameters calculated using the modelling of Tofts and Kermode. These included the volume transfer constant, the volume of the extravascular extracellular space per unit volume of tissue, the fractional plasma volume, the cerebral blood flow and the cerebral blood volume. Thus, dynamic contrast-enhanced T1-weighted MRI appears to be able to assess important permeability and perfusion characteristics in cerebral lesions in RRMS patients.

A particularly innovative aspect of the study by Yin and colleagues was the first application, to the analysis of cerebral MRI data from MS patients, of a histogram-based method (showing the distribution of pixels with the same intensity) of investigating permeability parameter distributions. Compared with the non-enhancing lesions, the histogram of the volume of the extravascular extracellular space per unit volume of tissue for the contrast-enhancing lesions was more Gaussian.[3] This suggests that this graphical method might be able to help distinguish between these lesion types.

There were no significant correlations between the above MRI biomarkers, on the one hand, and, on the other hand, either disease severity, as assessed by the Expanded Disability Status Scale (EDSS), or duration of illness. Although the Kurtzke EDSS takes into account the level of disability in eight functional systems, namely visual functions, brain stem functions, pyramidal functions, cerebellar functions, sensory functions, bowel and bladder functions, cerebral functions and an ambulation score, the overall quantitative score may not be sensitive enough to allow any underlying correlation between disease severity and the MRI biomarkers studied to be easily detected. On the other hand, it noteworthy that, in the recent 99m Tc-labelled bicisate cerebral single-photon emission computed tomography (SPECT) study of 25 patients with secondary progressive MS by Taghizadeh and colleagues, a significant association was reported between the level of cerebral perfusion impairment and the EDSS.[5]

Indeed, my colleagues and I have recently pointed out that, in addition to the types of MRI biomarkers measured by Yin and colleagues, there is a growing body of research showing changes in cerebral perfusion and cerebral blood volume in MS patients using SPECT and positron emission tomography (PET), with perfusion changes being observed in different MS subtypes, in those MS patients who have a clinically isolated syndrome, and at a very early stage of the illness.[6] MRI-based techniques clearly have the advantage over SPECT and PET, of not exposing patients to ionising radiation. On the other hand, as is well known, there has been concern expressed in some quarters over the safety of gadolinium-based contrast agents. In any case, the reduced cerebral blood flow observed in MS does not appear to be secondary to neuronal axon pathology; D'haeseleer and colleagues have suggested that cerebral hypoperfusion be considered to be a new pathophysiological concept in this illness.[7]

Overall, the study by Yin and colleagues has much to commend it. It needs to be repeated, preferably with larger cohorts. Also, as the authors themselves acknowledge, it would be of value to use this methodology to assess changes in cerebral perfusion and blood-brain barrier permeability in MS patients before and after putative treatments. This would particularly apply to treatment options aimed at reversing cerebral hypoperfusion, or at least some of its consequences.



 
  References Top

1.
Tofts P, Kermode AG. Measurement of the blood-brain barrier permeability and leakage space using dynamic MR imaging. 1. Fundamental concepts. Magn Reson Med 1991;17:357-67.  Back to cited text no. 1
    
2.
Young IR, Bryant DJ, Payne JA. Variations in slice shape and absorption as artifacts in the determination of tissue parameters in NMR imaging. Magn Reson Med 1985;2:355-89.  Back to cited text no. 2
[PUBMED]    
3.
Yin P, Xiong H, Liu Y, Sah SK, Zeng C, Wang J, et al. Measurement of the permeability, perfusion, and histogram characteristics in relapsing-remitting multiple sclerosis using dynamic contrast-enhanced MRI with extended Tofts linear model. Neurol India 2018;66:709-15.  Back to cited text no. 3
  [Full text]  
4.
Tofts PS. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J Magn Reson Imaging 1997;7:91-101.  Back to cited text no. 4
[PUBMED]    
5.
Taghizadeh AM, Nemati R, Chabi N, Salimipour H, Nabipour I, Assadi M. Brain perfusion imaging with voxel-based analysis in secondary progressive multiple sclerosis patients with a moderate to severe stage of disease: A boon for the workforce. BMC Neurol 2016;16:79.  Back to cited text no. 5
    
6.
Morris G, Berk M, Puri BK. A comparison of neuroimaging abnormalities in multiple sclerosis, major depression and chronic fatigue syndrome (myalgic encephalomyelitis): Is there a common cause? Mol Neurobiol 2018;55:3592-609.  Back to cited text no. 6
    
7.
D'haeseleer M, Hostenbach S, Peeters I, Sankari SE, Nagels G, De Keyser J, et al. Cerebral hypoperfusion: A new pathophysiologic concept in multiple sclerosis? J Cereb Blood Flow Metab 2015;35:1406-10.  Back to cited text no. 7
    




 

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