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Table of Contents    
Year : 2018  |  Volume : 66  |  Issue : 3  |  Page : 671-672

Quantification of blood brain barrier using DCE MRI in multiple sclerosis - Technical issues and its possible role in routine clinical practice

Department of Radiology, Fortis Memorial Research Institute, Gurugram, Haryana, India

Date of Web Publication15-May-2018

Correspondence Address:
Dr. Rakesh K Gupta
Department of Radiology, Fortis Memorial Research Institute, Gurugram, Haryana
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/0028-3886.232323

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How to cite this article:
Gupta RK. Quantification of blood brain barrier using DCE MRI in multiple sclerosis - Technical issues and its possible role in routine clinical practice. Neurol India 2018;66:671-2

How to cite this URL:
Gupta RK. Quantification of blood brain barrier using DCE MRI in multiple sclerosis - Technical issues and its possible role in routine clinical practice. Neurol India [serial online] 2018 [cited 2022 Jul 3];66:671-2. Available from: https://www.neurologyindia.com/text.asp?2018/66/3/671/232323

Dynamic contrast-enhanced (DCE) MRI gives quantitative information about the integrity of the vascular system and has been used in brain tumors, infections and multiple sclerosis.[1],[2],[3],[4] It has also been used to quantify neoangiogenesis in brain tumors and infections, in addition to quantification of blood brain barrier (BBB) disruption.[2],[3] The parameter of interest in BBB integrity is the transfer constant, Ktrans,[1] which describes the transfer rate of molecules from the plasma space into the interstitial space. As the BBB permeability is dependent on the size of the molecules, interpretation of Ktrans requires consideration of the structural and physiological changes at play with respect to BBB as well as the contrast agent (CA) being used to quantify Ktrans.[1] Most applications of DCE in the brain have focused on imaging of lesions associated a relatively high BBB breakdown, like tumors. Ktrans values in the intact or subtly damaged BBB are at least one to two orders of magnitude lower than those found in areas of highly compromised BBB.[1],[2],[3] There is technical non-uniformity in its quantification with variability in its implementation on the scanners. This results in cross-validation across the vendors, which may result in inappropriate cross-comparison of various studies published in the literature.[1],[2],[3]

Despite all the issues associated with technique, it has been widely used in the evaluation of a number of brain pathologies, including multiple sclerosis. There are a number of studies suggesting that altered permeability of the BBB in normal-appearing white matter, as measured by MRI, may provide novel pathological information on inflammation in optic neuritis and multiple sclerosis (MS), possibly providing a biomarker of the present level of multiple sclerosis-related central nervous system (CNS) inflammation.[4],[5],[6],[7],[8],[9] Currently, the most widely used measures of MS disease activity are the occurrence of new MRI lesions and/or clinical relapses, but these measures do not always correlate well with long-term disability outcomes in clinical MS trials. This suggests the existence of ongoing subclinical disease activity even in the absence of relapses or conventional MRI visible activity. Hence, a new marker of low-grade MS disease activity could have many useful applications, i.e., in the subclinical disease activity monitoring or in identification of inadequate treatment response before the occurrence of next relapse.[6],[7],[8] Furthermore, quantification of BBB permeability may constitute an early prognostic indicator in the pathogenesis of MS, while MRI features such as MS plaques, reduction of N-acetyl-aspartate, reduced magnetic transfer ratio (MTR), changes in T1 values, and tissue atrophy may be considered as consequences of a long lasting inflammation.[6],[7] It has also been shown that changes in permeability of the normal appearing white matter in patients with optic neuritis who subsequently start demonstrating lesions of MS on follow up scans, can be predicted using BBB quantification.[8]

Yin et al., have quantified various hemodynamic and kinetic parameters in enhancing and non-enhancing plaques as well as normal appearing white matter in patients with relapsing remitting multiple sclerosis (RRMS).[4] They concluded that the DCE-MRI measures the permeability and perfusion characteristics in MS lesions and normal appearing white matter (NAWM) regions. The K trans, Ve, Vp, cerebral blood flow (CBF), and cerebral blood volume (CBV) parameters of contrast enhancing lesions were significantly higher than that of non-enhancing lesions.[4] which is on the expected lines. However, the lack of significant correlation among the biomarkers with the expanded disability status scale (EDSS) scores and the disease duration raises doubt about its use in clinical management of patients suffering from RRMS.[4]

Cremar et al., in 2014, have emphasized the importance of BBB quantification in MS and have shown that recent relapse coincides with a higher permeability in non-enhancing lesions, periventricular normal appearing white matter and thalamic gray matter, and reflects the underlying ongoing inflammatory process.[6] Recently, Cramer et al., have also predicted early suboptimal treatment response in 35 patients with RRMS, measured by quantification of BBB permeability using DCE-MRI.[9]

I conclude that DCE MRI appears to be useful in the evaluation of normal appearing white matter and in therapeutic response assessment in MS. The technique needs to be more stable and vendor independent so that imaging results from different studies across institutions may be comparable in the future.

  References Top

Samuel R. Barnes1, Thomas S.C. Ng1, Montagne A, Law M, et al. Optimal acquisition and modeling parameters for accurate assessment of low Ktrans blood-brain barrier permeability using dynamic contrast-enhanced MRI Magn Reson Med 2016;75:1967-77.  Back to cited text no. 1
Sahoo P, Rathore RK, Awasthi R, Roy B, Verma S, Rathore D, et al. Subcompartmentalization of extracellular extravascular space (EES) into permeability and leaky space with local arterial input function (AIF) results in improved discrimination between high- and low-grade glioma using dynamic contrast-enhanced (DCE) MRI. J Magn Reson Imaging 2013;38:677-88.  Back to cited text no. 2
Gupta RK, Awasthi R, Garg RK, Kumar N, Gupta PK, Singh AK, et al. T1-weighted dynamic contrast-enhanced MR evaluation of different stages of neurocysticercosis and its relationship with serum MMP-9 expression. AJNR Am J Neuroradiol 2013;34:997-1003.  Back to cited text no. 3
Yin P, Xiong H, Liu Y, Sah SK, Zeng C, Wang Z, Li. Measurement of the permeability, perfusion, and histogram characteristics in relapsing-remitting multiple sclerosis using dynamic contrast-enhanced MRI with extended Tofts linear model. Neurology India 2018;66:709-15.  Back to cited text no. 4
Gaitán MI, Shea CD, Evangelou IE, Stone RD, Fenton KM, Bielekova B, et al. Evolution of the blood-brain barrier in newly forming multiple sclerosis lesions. Ann Neurol 2011;70:22-9.  Back to cited text no. 5
Cramer SP, Larsson HB. Accurate determination of blood-brain barrier permeability using dynamic contrast-enhanced T1-weighted MRI: a simulation and in vivo study on healthy subjects and multiple sclerosis patients. J Cereb Blood Flow Metab 2014;34:1655-65.  Back to cited text no. 6
Cramer SP, Simonsen H, Frederiksen JL, Rostrup E, Larsson HB. Abnormal blood-brain barrier permeability in normal appearing white matter in multiple sclerosis investigated by MRI. Neuroimage Clin 2013;4:182-9.  Back to cited text no. 7
Cramer SP, Modvig S, Simonsen HJ, Frederiksen JL, Larsson HB. Permeability of the blood-brain barrier predicts conversion from optic neuritis to multiple sclerosis. Brain 2015;138:2571-83.  Back to cited text no. 8
Cramer SP, Simonsen HJ, Varatharaj A, Galea I, Frederiksen JL, Larsson HBW. Permeability of the blood-brain barrier predicts no evidence of disease activity at two years after natalizumab or fingolimod treatment in relapsing-remitting multiple sclerosis. Ann Neurol 2018. doi: 10.1002/ana.25219.  Back to cited text no. 9


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