The relationship between white matter fiber damage and gray matter perfusion in large-scale functionally defined networks in multiple sclerosis

Abstract

Background:

Recent studies utilizing perfusion as a surrogate of cortical integrity show promise for overall cognition, but the association between white matter (WM) damage and gray matter (GM) integrity in specific functional networks is not previously studied.

Objective:

To investigate the relationship between WM fiber integrity and GM node perfusion within six functional networks of relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS) patients.

Methods:

Magnetic resonance imaging (MRI) and neurocognitive testing were performed on 19 healthy controls (HC), 39 RRMS, and 45 SPMS patients. WM damage extent and severity were quantified with T2-hyper/T1-hypointense (T2h/T1h) lesion volume and degree of perfusion reduction in lesional and normal-appearing white matter (NAWM), respectively. A two-step linear regression corrected for confounders was employed.

Results:

Cognitive impairment was present in 20/39 (51%) RRMS and 25/45 (53%) SPMS patients. GM node perfusion was associated with WM fiber damage severity (WM hypoperfusion) within each network—including both NAWM (R² = 0.67–0.89, p < 0.0001) and T2h (R² = 0.39–0.62, p < 0.0001) WM regions—but was not significantly associated (p > 0.01) with WM fiber damage extent (i.e. T2h/T1h lesion volumes).

Conclusion:

Overall, GM node perfusion was associated with severity rather than extent of WM network damage, supporting a primary etiology of GM hypoperfusion.

Keywords

Multiple sclerosis magnetic resonance imaging perfusion functional network node cognition

Get full access to this article

View all access options for this article.

References

Chiaravalloti

DeLuca

Cognitive impairment in multiple sclerosis. Lancet Neurol 2008; 7: 1139–1151.

Rao

Leo

Bernardin

et al . Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction. Neurology 1991; 41: 685–691.

Compston

Coles

Multiple sclerosis. Lancet 2002; 359: 1221–1231.

Rocca

Amato

De Stefano

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

Battaglini

Giorgio

Stromillo

et al . Voxel-wise assessment of progression of regional brain atrophy in relapsing-remitting multiple sclerosis. J Neurol Sci 2009; 282: 55–60.

Charil

Dagher

Lerch

et al . Focal cortical atrophy in multiple sclerosis: Relation to lesion load and disability. Neuroimage 2007; 34: 509–517.

Galego

Gouveia

Batista

et al . Brain atrophy and physical disability in primary progressive multiple sclerosis: A volumetric study. Neuroradiol J 2015; 28: 354–358.

Morgen

Sammer

Courtney

et al . Evidence for a direct association between cortical atrophy and cognitive impairment in relapsing-remitting MS. Neuroimage 2006; 30: 891–898.

Steenwijk

Daams

Pouwels

et al . Unraveling the relationship between regional gray matter atrophy and pathology in connected white matter tracts in long-standing multiple sclerosis. Hum Brain Mapp 2015; 36: 1796–1807.

10.

Inglese

Park

Johnson

et al . Deep gray matter perfusion in multiple sclerosis: Dynamic susceptibility contrast perfusion magnetic resonance imaging at 3 T. Arch Neurol 2007; 64: 196–202.

11.

Debernard

Melzer

Van Stockum

et al . Reduced grey matter perfusion without volume loss in early relapsing-remitting multiple sclerosis. J Neurol Neurosurg Psychiatry 2013; 85: 544–551.

12.

Aviv

Francis

Tenenbein

et al . Decreased frontal lobe gray matter perfusion in cognitively impaired patients with secondary-progressive multiple sclerosis detected by the bookend technique. AJNR Am J Neuroradiol 2012; 33: 1779–1785.

13.

Hojjat

Cantrell

Carroll

et al . Perfusion reduction in the absence of structural differences in cognitively impaired versus unimpaired RRMS patients. Mult Scler 2016; 22: 1685–1694.

14.

Jehna

Langkammer

Khalil

et al . An exploratory study on the spatial relationship between regional cortical volume changes and white matter integrity in multiple sclerosis. Brain Connect 2013; 3: 255–264.

15.

Preziosa

Rocca

Pagani

et al . Structural MRI correlates of cognitive impairment in patients with multiple sclerosis: A Multicenter Study. Hum Brain Mapp 2016; 37: 1627–1644.

16.

Figley

Bhullar

Courtney

et al . Probabilistic atlases of default mode, executive control and salience network white matter tracts: An fMRI-guided diffusion tensor imaging and tractography study. Front Hum Neurosci 2015; 9: 585.

17.

Vakil

Lee

Mouannes-Srour

et al . Cerebrovascular occlusive disease: Quantitative cerebral blood flow using dynamic susceptibility contrast MR imaging correlates with quantitative H2[15O] PET. Radiology 2013; 266: 879–886.

18.

Shirer

Ryali

Rykhlevskaia

et al . Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cereb Cortex 2012; 22: 158–165.

19.

Valverde

Oliver

Llado

A white matter lesion-filling approach to improve brain tissue volume measurements. Neuroimage Clin 2014; 6: 86–92.

20.

Rao

Martin

Huelin

et al . Correlations between MRI and Information Processing Speed in MS: A meta-analysis. Mult Scler Int 2014; 2014: 975803.

21.

Hojjat

Kincal

Vitorino

et al . Cortical perfusion alteration in normal-appearing gray matter is most sensitive to disease progression in relapsing-remitting multiple sclerosis. AJNR Am J Neuroradiol 2016; 37: 1454–1461.

22.

De Groot

Verhaaren

De Boer

et al . Changes in normal-appearing white matter precede development of white matter lesions. Stroke 2013; 44: 1037–1042.

23.

Barkhof

The clinico-radiological paradox in multiple sclerosis revisited. Curr Opin Neurol 2002; 15: 239–245.

24.

Jonkman

Fleysher

Steenwijk

et al . Ultra-high field MTR and qR2* differentiates subpial cortical lesions from normal-appearing gray matter in multiple sclerosis. Mult Scler 2015; 22: 1306–1314.

25.

Fisher

Lee

Nakamura

et al . Gray matter atrophy in multiple sclerosis: A longitudinal study. Ann Neurol 2008; 64: 255–265.

26.

Trapp

Peterson

Ransohoff

et al . Axonal transection in the lesions of multiple sclerosis. N Engl J Med 1998; 338: 278–285.

27.

Simon

Ischemia and multiple sclerosis: Perfusion MR imaging provides insight into an underexplored pathophysiology. AJNR Am J Neuroradiol 2005; 26: 1306–1308.

28.

Nikic

Merkler

Sorbara

et al . A reversible form of axon damage in experimental autoimmune encephalomyelitis and multiple sclerosis. Nat Med 2011; 17: 495–499.

29.

D’Haeseleer

Cambron

Vanopdenbosch

et al . Vascular aspects of multiple sclerosis. Lancet Neurol 2011; 10: 657–666.

30.

Calabrese

Gallo

Magnetic resonance evidence of cortical onset of multiple sclerosis. Mult Scler 2009; 15: 933–941.

31.

Kanda

Ishii

Kawaguchi

et al . High signal intensity in the dentate nucleus and Globus Pallidus on unenhanced T1-weighted MR images: Relationship with increasing cumulative dose of a gadolinium-based contrast material. Radiology 2014; 270: 834–841.

32.

McDonald

Kallmes

et al . Intracranial gadolinium deposition after contrast-enhanced MR imaging. Radiology 2015; 275: 772–782.

33.

Essig

Nguyen

Shiroishi

et al . Perfusion MRI: The five most frequently asked clinical questions. AJR Am J Roentgenol 2013; 201: W495–W510.

34.

Shin

Horowitz

Ragin

et al . Quantitative cerebral perfusion using dynamic susceptibility contrast MRI: Evaluation of reproducibility and age- and gender-dependence with fully automatic image postprocessing algorithm. Magn Reson Med 2007; 58: 1232–1241.

35.

Amann

Achtnichts

Hirsch

et al . 3D GRASE arterial spin labelling reveals an inverse correlation of cortical perfusion with the white matter lesion volume in MS. Mult Scler 2012; 18: 1570–1576.

36.

Biller

Reuter

Patenaude

et al . Responses of the human brain to mild dehydration and rehydration explored in vivo by 1H-MR imaging and spectroscopy. AJNR Am J Neuroradiol 2015; 36: 2277–2284.

37.

Kumar

Yadav

Palomares

et al . Reduced regional brain cortical thickness in patients with heart failure. PLoS ONE 2015; 10: e0126595.

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

0.33 MB