Sage Journals: Discover world-class research

Abstract

Background:

Volumetric MRI surrogate markers of disease progression are lacking.

Objective:

To establish cut-off values of brain volume loss able to discriminate between healthy controls and MS patients.

Methods:

In total, 386 patients after first demyelinating event suggestive of MS (CIS), 964 relapsing-remitting MS (RRMS) patients, 63 secondary-progressive MS (SPMS) patients and 58 healthy controls were included in this longitudinal study. A total of 11,438 MRI scans performed on the same MRI scanner with the same protocol were analysed. Annualised percentage changes of whole brain, grey matter, thalamus and corpus callosum volumes were estimated. We investigated cut-offs able to discriminate between healthy controls and MS patients.

Results:

At a predefined specificity of 90%, the annualised percentage change cut-off of corpus callosum volume (−0.57%) was able to distinguish between healthy controls and patients with the highest sensitivity (51% in CIS, 48% in RRMS and 42% in SPMS patients). Lower sensitivities (22%−49%) were found for cut-offs of whole brain, grey matter and thalamic volume loss. Among CIS and RRMS patients, cut-offs were associated with greater accumulation of disability.

Conclusion:

We identified cut-offs of annualised global and regional brain volume loss rates able to discriminate between healthy controls and MS patients.

Keywords

Multiple sclerosis MRI brain atrophy cut-off value disability

Get full access to this article

View all access options for this article.

References

Sormani

Arnold

De Stefano

Treatment effect on brain atrophy correlates with treatment effect on disability in multiple sclerosis. Ann Neurol 2014; 75(1): 43–49.

Azevedo

Pelletier

Whole-brain atrophy: Ready for implementation into clinical decision-making in multiple sclerosis?

Curr Opin Neurol 2016; 29(3): 237–242.

De Stefano

Airas

Grigoriadis

et al . Clinical relevance of brain volume measures in multiple sclerosis. CNS Drugs 2014; 28(2): 147–156.

Zivadinov

Jakimovski

Gandhi

et al . Clinical relevance of brain atrophy assessment in multiple sclerosis. Implications for its use in a clinical routine. Expert Rev Neurother 2016; 16(7): 777–793.

Uher

Vaneckova

Sobisek

et al . Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year disability in multiple sclerosis. Mult Scler 2017; 23(1): 51–61.

Rocca

Amato

De Stefano

et al . Clinical and imaging assessment of cognitive dysfunction in multiple sclerosis. Lancet Neurol 2015; 14(3): 302–317.

Benedict

Zivadinov

Risk factors for and management of cognitive dysfunction in multiple sclerosis. Nat Rev Neurol 2011; 7(6): 332–342.

Uher

Vaneckova

Sormani

et al . Identification of multiple sclerosis patients at highest risk of cognitive impairment using an integrated brain magnetic resonance imaging assessment approach. Eur J Neurol 2017; 24(2): 292–301.

De Stefano

Stromillo

Giorgio

et al . Establishing pathological cut-offs of brain atrophy rates in multiple sclerosis. J Neurol Neurosurg Psychiatr 2016; 87(1): 93–99.

10.

Kalincik

Vaneckova

Tyblova

et al . Volumetric MRI markers and predictors of disease activity in early multiple sclerosis: A longitudinal cohort study. PLoS ONE 2012; 7(11): e50101.

11.

Uher

Horakova

Bergsland

et al . MRI correlates of disability progression in patients with CIS over 48 months. Neuroimage Clin 2014; 6: 312–319.

12.

Uher

Havrdova

Sobisek

et al . Is no evidence of disease activity an achievable goal in MS patients on intramuscular interferon beta-1a treatment over long-term follow-up? Mult Scler 2017; 23(2): 242–252.

13.

Uher

Horakova

Kalincik

et al . Early magnetic resonance imaging predictors of clinical progression after 48 months in clinically isolated syndrome patients treated with intramuscular interferon beta-1a. Eur J Neurol 2015; 22(7): 1113–1123.

14.

Havrdova

Zivadinov

Krasensky

et al . Randomized study of interferon beta-1a, low-dose azathioprine, and low-dose corticosteroids in multiple sclerosis. Mult Scler 2009; 15(8): 965–976.

15.

Horakova

Cox

Havrdova

et al . Evolution of different MRI measures in patients with active relapsing-remitting multiple sclerosis over 2 and 5 years: A case-control study. J Neurol Neurosurg Psychiatry 2008; 79(4): 407–414.

16.

Zivadinov

Uher

Hagemeier

et al . A serial 10-year follow-up study of brain atrophy and disability progression in RRMS patients. Mult Scler 2016; 22(13): 1709–1718.

17.

Rocca

Battaglini

Benedict

et al . Brain MRI atrophy quantification in MS: From methods to clinical application. Neurology 2017; 88(4): 403–413.

18.

Zivadinov

Havrdova

Bergsland

et al . Thalamic atrophy is associated with development of clinically definite multiple sclerosis. Radiology 2013; 268(3): 831–841.

19.

Geurts

Calabrese

Fisher

et al . Measurement and clinical effect of grey matter pathology in multiple sclerosis. Lancet Neurol 2012; 11(12): 1082–1092.

20.

Granberg

Martola

Bergendal

et al . Corpus callosum atrophy is strongly associated with cognitive impairment in multiple sclerosis: Results of a 17-year longitudinal study. Mult Scler 2015; 21(9): 1151–1158.

21.

Klawiter

Ceccarelli

Arora

et al . Corpus callosum atrophy correlates with gray matter atrophy in patients with multiple sclerosis. J Neuroimaging 2015; 25(1): 62–67.

22.

Garg

Reddel

Miller

et al . The corpus callosum in the diagnosis of multiple sclerosis and other CNS demyelinating and inflammatory diseases. J Neurol Neurosurg Psychiatry 2015; 86(12): 1374–1382.

23.

Uher

Krasensky

Vaneckova

et al . A novel semiautomated pipeline to measure brain atrophy and lesion burden in multiple sclerosis: A long-term comparative study. J Neuroimaging 2017; 27: 620–629.

24.

Schippling

Ostwaldt

Suppa

et al . Global and regional annual brain volume loss rates in physiological aging. J Neurol 2017; 264(3): 520–528.

25.

Vaneckova

Kalincik

Krasensky

et al . Corpus callosum atrophy–a simple predictor of multiple sclerosis progression: A longitudinal 9-year study. Eur Neurol 2012; 68(1): 23–27.

26.

Uher

Horakova

Tyblova

et al . Increased albumin quotient (QAlb) in patients after first clinical event suggestive of multiple sclerosis is associated with development of brain atrophy and greater disability 48 months later. Mult Scler 2016; 22(6): 770–781.

27.

Smith

Zhang

Jenkinson

et al . Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage 2002; 17(1): 479–489.

28.

Miller

Soon

Fernando

et al . MRI outcomes in a placebo-controlled trial of natalizumab in relapsing MS. Neurology 2007; 68(17): 1390–1401.

29.

Sormani

De Stefano

Francis

et al . Fingolimod effect on brain volume loss independently contributes to its effect on disability. Mult Scler 2015; 21(7): 916–924.

30.

Arnold

Fisher

Brinar

et al . Superior MRI outcomes with alemtuzumab compared with subcutaneous interferon beta-1a in MS. Neurology 2016; 87(14): 1464–1472.

31.

Kappos

De Stefano

Freedman

et al . Inclusion of brain volume loss in a revised measure of ‘no evidence of disease activity’ (NEDA-4) in relapsing-remitting multiple sclerosis. Mult Scler 2016; 22(10): 1297–1305.

32.

Rovaris

Comi

Filippi

Can glatiramer acetate reduce brain atrophy development in multiple sclerosis?

J Neurol Sci 2005; 233(1–2): 139–143.

33.

Zivadinov

Reder

Filippi

et al . Mechanisms of action of disease-modifying agents and brain volume changes in multiple sclerosis. Neurology 2008; 71(2): 136–144.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.60 MB

0.30 MB

0.26 MB

0.60 MB

Pathological cut-offs of global and regional brain volume loss in multiple sclerosis

Abstract

Background:

Objective:

Methods:

Results:

Conclusion:

Keywords

Get full access to this article

References

Supplementary Material