Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on sleep in brain health

LIVE: Thursday 2nd May 2024, 18:00-19:30 (CEST)

Quality sleep is essential for health. But what happens to our brains when sleep patterns are disturbed? Join our experts to explore the interplay between sleep disruption and neurological diseases, and the questions that you need to be asking your patients to help you prevent the harmful effects of sleep deprivation.
ADVANCED SEARCH
Log in
Top
Neuroradiology
Published in: Neuroradiology 8/2017

01-08-2017 | Functional Neuroradiology

Normal appearing white matter permeability: a marker of inflammation and information processing speed deficit among relapsing remitting multiple sclerosis patients

Authors: Eldar Eftekhari, Seyed-Parsa Hojjat, Rita Vitorino, Timothy J. Carroll, Charles Grady Cantrell, Liesly Lee, Matthew W. Taylor, Sarah A. Morrow, Haddas Benhabib, Richard I. Aviv, Andrea Kassner

Published in: Neuroradiology | Issue 8/2017

Login to get access

Abstract

Purpose

Blood-brain barrier breakdown (BBBB) occurs in relapsing remitting multiple sclerosis (RRMS). Relative recirculation (rR), a BBBB surrogate, may show inflammation undetectable by gadolinium. We compared normal appearing white matter (NAWM) rR in patients with and without disability measured with Symbol Digit Modalities Test and the Expanded Disability Status Scale (EDSS).

Methods

Thirty-nine RRMS patients were prospectively recruited and classified as impaired or non-impaired based on the SDMT and EDSS threshold ≥3. Significant demographic, MRI structural and regional rR characteristics were advanced into multivariate analysis to assess the association with impairment of cognition and EDSS. Bonferroni corrected p < 0.025 was applied to demographic and rR group comparisons; p < 0.05 was used in the final multivariate logistic regression.

Results

rR was higher in NAWM (p = 0.012), NAGM (p = 0.004), and basal ganglia (p = 0.007) in cognitively impaired versus non-impaired patients. The difference between NAWM and T2HL rR was significant in cognitively non-impaired patients and approximated that of T2HL in impairment (0.084 vs. 0.075, p = 0.008; 0.118 vs. 0.101, p = 0.091, respectively). After adjusting for confounders, rR elevation for NAWM (OR 1.777; 95% CI 1.068–2.956; p = 0.026), NAGM (OR 2.138; 1.100–4.157; p = 0.025), and basal ganglia (OR 2.192; 1.120–4.289; p = 0.022) remained significantly predictive of cognitive impairment. NAWM area under the curve (AUC) for cognitive impairment was 0.783. No significant group differences or associations were seen for rR and EDSS impairment. No NAGM and cortical lesion rR difference was present within any of the impaired or non-impaired groups.

Conclusion

rR elevation in NAWM, NAGM, and basal ganglia appears sensitive to cognitive impairment but not EDSS.
Literature
1.
Amato MP, Zipoli V, Portaccio E (2006) Multiple sclerosis-related cognitive changes: a review of cross-sectional and longitudinal studies. J Neurol Sci 245:41–46CrossRefPubMed
2.
Camp SJ, Stevenson VL, Thompson AJ, Miller DH, Borras C, Auriacombe S et al (1999) Cognitive function in primary progressive and transitional progressive multiple sclerosis: a controlled study with MRI correlates. Brain 122(Pt 7):1341–1348CrossRefPubMed
3.
Steenwijk MD, Daams M, Pouwels PJ, Balk LJ, Tewarie PK, Geurts JJ et al (2015) Unraveling the relationship between regional gray matter atrophy and pathology in connected white matter tracts in long-standing multiple sclerosis. Hum Brain Mapp 36:1796–1807CrossRefPubMed
4.
Mesaros S, Rocca MA, Riccitelli G, Pagani E, Rovaris M, Caputo D et al (2009) Corpus callosum damage and cognitive dysfunction in benign ms. Hum Brain Mapp 30:2656–2666CrossRefPubMed
5.
Schmierer K, Scaravilli F, Altmann DR, Barker GJ, Miller DH (2004) Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain. Ann Neurol 56:407–415CrossRefPubMed
6.
Bellmann-Strobl J, Wuerfel J, Aktas O, Dorr J, Wernecke KD, Zipp F et al (2009) Poor pasat performance correlates with MRI contrast enhancement in multiple sclerosis. Neurology 73:1624–1627CrossRefPubMed
7.
Filippi M, Rocca MA, Benedict RH, DeLuca J, Geurts JJ, Rombouts SA et al (2010) The contribution of MRI in assessing cognitive impairment in multiple sclerosis. Neurology 75:2121–2128CrossRefPubMedPubMedCentral
8.
Zivadinov R, Leist TP (2005) Clinical-magnetic resonance imaging correlations in multiple sclerosis. J Neuroimaging 15:10S–21SCrossRefPubMed
9.
Silver NC, Good CD, Barker GJ, MacManus DG, Thompson AJ, Moseley IF et al (1997) Sensitivity of contrast enhanced MRI in multiple sclerosis. Effects of gadolinium dose, magnetization transfer contrast and delayed imaging. Brain 120(Pt 7):1149–1161CrossRefPubMed
10.
Jackson A, Kassner A, Annesley-Williams D, Reid H, Zhu XP, Li KL (2002) Abnormalities in the recirculation phase of contrast agent bolus passage in cerebral gliomas: comparison with relative blood volume and tumor grade. AJNR Am J Neuroradiol 23:7–14PubMed
11.
Kassner A, Mandell DM, Mikulis DJ (2011) Measuring permeability in acute ischemic stroke. Neuroimaging Clin N Am 21:315–325 x-xi CrossRefPubMed
12.
Kassner A, Zhu XP, Li KL, Jackson A (2003) Neoangiogenesis in association with moyamoya syndrome shown by estimation of relative recirculation based on dynamic contrast-enhanced mr images. AJNR Am J Neuroradiol 24:810–818PubMed
13.
Eilaghi A, Kassner A, Sitartchouk I, Francis PL, Jakubovic R, Feinstein A et al (2013) Normal-appearing white matter permeability distinguishes poor cognitive performance in processing speed and working memory. AJNR Am J Neuroradiol 34:2119–2124CrossRefPubMed
14.
Goldman MD, Motl RW, Rudick RA (2010) Possible clinical outcome measures for clinical trials in patients with multiple sclerosis. Ther Adv Neurol Disord 3:229–239CrossRefPubMedPubMedCentral
15.
Martin CL, Phillips BA, Kilpatrick TJ et al (2006) Gait and balance impairment in early multiple sclerosis in the absence of clinical disability. Mult Scler J 12:620–628CrossRef
16.
Winsen LMV, Kragt JJ, Hoogervorst EL et al (2010) Outcome measurement in multiple sclerosis: detection of clinically relevant improvement. Mult Scler J 16:604–610CrossRef
17.
Rudick RA, Lee J-C, Nakamura K, Fisher E (2009) Gray matter atrophy correlates with MS disability progression measured with MSFC but not EDSS. J Neurol Sci 282:106–111CrossRefPubMed
18.
Schwid SR, Goodman AD, Apatoff BR et al (2000) Are quantitative functional measures more sensitive to worsening MS than traditional measures? Neurology 55:1901–1903CrossRefPubMed
19.
Cohen RA, Kessler HR, Fischer M (1993) The extended disability status scale (EDSS) as a predictor of impairments of functional activities of daily living in multiple sclerosis. J Neurol Sci 115:132–135CrossRefPubMed
20.
Ruggieri RM, Palermo R, Vitello G et al (2003) Cognitive impairment in patients suffering from relapsing-remitting multiple sclerosis with EDSS <= 3.5. Acta Neurol Scand 108:323–326CrossRefPubMed
21.
Mesaros S, Rocca MA, Kacar K et al (2012) Diffusion tensor MRI tractography and cognitive impairment in multiple sclerosis. Neurology 78:969–975CrossRefPubMed
22.
Grant I, Mcdonald WI, Trimble MR et al (1984) Deficient learning and memory in early and middle phases of multiple sclerosis. J Neurol Neurosurg Psychiatry 47:250–255CrossRefPubMedPubMedCentral
23.
Poser S (1978) Multiple sclerosis: an analysis of 812 cases by means of electronic data processing. Springer, BerlinCrossRef
24.
Charil A, Filippi M (2007) Inflammatory demyelination and neurodegeneration in early multiple sclerosis. J Neurol Sci 259:7–15CrossRefPubMed
25.
Rao SM (1991) A manual for the Brief Repeatable Battery of Neuropsychological Tests in Multiple Sclerosis. Medical College of Wisconsin, Milwaukee
26.
Benedict RH, Morrow S, Rodgers J, Hojnacki D, Bucello MA, Zivadinov R et al (2014) Characterizing cognitive function during relapse in multiple sclerosis. Mult Scler 20(13):1745–1752CrossRefPubMed
27.
Morrow SA, Jurgensen S, Forrestal F, Munchauer FE, Benedict RH (2011) Effects of acute relapses on neuropsychological status in multiple sclerosis patients. J Neurol 258(9):1603–1608CrossRefPubMed
28.
Parmenter BA, Weinstock-Guttman B, Garg N, Munschauer F, Benedict RHB (2007) Screening for cognitive impairment in multiple sclerosis using the symbol digit modalities test. Mult Scler 13(1):52–57CrossRefPubMed
29.
Van Schependom J, D’hooghe MB, Cleynhens K, D’hooge M, Haelewyck MC, De Keyser J et al (2014) The symbol digit modalities test as sentinel test for cognitive impairment in multiple sclerosis. Eur J Neurol 21(9):1219–1e72CrossRefPubMed
30.
Benedict RHB, Fischer JS, Archibald CJ, Arnett PA, Beatty WW, Bobholz J et al (2002) Minimal neuropsychological assessment of MS patients: a consensus approach. Clin Neuropsychol 16:381–397CrossRefPubMed
31.
Rao SM (1991) A manual for the brief, repeatable battery of neuropsychological tests in multiplesclerosis unpublished manual. Medical College of Wisconsin, Milwaukee
32.
Berrigan LI, Fisk JD, Walker LA, Wojtowicz M, Rees LM, Freedman MS, Marrie RA (2014) Reliability of regression-based normative data for the oral symbol digit modalities test: an evaluation of demographic influences, construct validity, and impairment classification rates in multiple sclerosis samples. Clin Neuropsychol 28(2):281–299CrossRefPubMed
33.
34.
Robb RA, Hanson DP, Karwoski RA, Larson AG, Workman EL, Stacy MC (1989) Analyze: a comprehensive, operator-interactive software package for multidimensional medical image display and analysis. Comput Med Imaging Graph 13:433–454CrossRefPubMed
35.
Wu S, Thornhill RE, Chen S, Rammo W, Mikulis DJ, Kassner A (2009) Relative recirculation: a fast, model-free surrogate for the measurement of blood-brain barrier permeability and the prediction of hemorrhagic transformation in acute ischemic stroke. Investig Radiol 44:662–668CrossRef
36.
Rosen BR, Belliveau JW, Vevea JM, Brady TJ (1990) Perfusion imaging with nmr contrast agents. Magn Reson Med 14:249–265CrossRefPubMed
37.
Kassner A, Annesley DJ, Zhu XP, Li KL, Kamaly-Asl ID, Watson Y et al (2000) Abnormalities of the contrast re-circulation phase in cerebral tumors demonstrated using dynamic susceptibility contrast-enhanced imaging: a possible marker of vascular tortuosity. J Magn Reson Imaging 11:103–113CrossRefPubMed
38.
Savettieri G, Messina D, Andreoli V et al (2004) Gender-related effect of clinical and genetic variables on the cognitive impairment in multiple sclerosis. J Neurol 251:1208–1214CrossRefPubMed
39.
Zeis T, Graumann U, Reynolds R, Schaeren-Wiemers N (2008) Normal-appearing white matter in multiple sclerosis is in a subtle balance between inflammation and neuroprotection. Brain 131:288–303CrossRefPubMed
40.
Hauser SL, Oksenberg JR (2006) The neurobiology of multiple sclerosis: genes, inflammation, and neurodegeneration. Neuron 52:61–76CrossRefPubMed
41.
Kutzelnigg A, Lucchinetti CF, Stadelmann C, Bruck W, Rauschka H, Bergmann M et al (2005) Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain 128:2705–2712CrossRefPubMed
42.
Lassmann H (2007) Multiple sclerosis: is there neurodegeneration independent from inflammation? J Neurol Sci 259:3–6CrossRefPubMed
43.
44.
Bo L, Vedeler CA, Nyland H, Trapp BD, Mork SJ (2003) Intracortical multiple sclerosis lesions are not associated with increased lymphocyte infiltration. Mult Scler 9:323–331CrossRefPubMed
45.
van Horssen J, Brink BP, de Vries HE, van der Valk P, Bo L (2007) The blood-brain barrier in cortical multiple sclerosis lesions. J Neuropathol Exp Neurol 66:321–328CrossRefPubMed
46.
Merkler D, Ernsting T, Kerschensteiner M, Bruck W, Stadelmann C (2006) A new focal eae model of cortical demyelination: multiple sclerosis-like lesions with rapid resolution of inflammation and extensive remyelination. Brain 129:1972–1983CrossRefPubMed
47.
Albert M, Antel J, Bruck W, Stadelmann C (2007) Extensive cortical remyelination in patients with chronic multiple sclerosis. Brain Pathol 17:129–138CrossRefPubMed
48.
Seewann A, Vrenken H, Kooi EJ, van der Valk P, Knol DL, Polman CH et al (2011) Imaging the tip of the iceberg: visualization of cortical lesions in multiple sclerosis. Mult Scler 17:1202–1210CrossRefPubMed
49.
Drake AS, Weinstock-Guttman B, Morrow SA, Hojnacki D, Munschauer FE, Benedict RH (2010) Psychometrics and normative data for the multiple sclerosis functional composite: replacing the pasat with the symbol digit modalities test. Mult Scler 16:228–237CrossRefPubMed
50.
Janculjak D, Mubrin Z, Brinar V, Spilich G (2002) Changes of attention and memory in a group of patients with multiple sclerosis. Clin Neurol Neurosurg 104:221–227CrossRefPubMed
51.
Gaudino EA, Chiaravalloti ND, DeLuca J, Diamond BJ (2001) A comparison of memory performance in relapsing–remitting, primary progressive and secondary progressive, multiple sclerosis. Neuropsychiatry Neuropsychol Behav Neurol 14:32–44PubMed
52.
Lengenfelder J, Chiaravalloti ND, Ricker JH, Deluca J (2003) Deciphering components of impaired working memory in multiple sclerosis. Cogn Behav Neurol 16:28–39CrossRefPubMed
53.
Rosti E, Hämäläinen P, Koivisto K, Hokkanen L (2007) PASAT in detecting cognitive impairment in relapsing-remitting MS. Appl Neuropsychol 14:101–112CrossRefPubMed
54.
Kalmar JH, Gaudino EA, Moore NB et al (2008) The relationship between cognitive deficits and everyday functional activities in multiple sclerosis. Neuropsychology 22:442–449CrossRefPubMed
55.
Bergendal G, Fredrikson S, Almkvist O (2007) Selective decline in information processing in subgroups of multiple sclerosis: an 8-year longitudinal study. Eur Neurol 57:193–202CrossRefPubMed
56.
Schwid SR, Goodman AD, Weinstein A et al (2007) Cognitive function in relapsing multiple sclerosis: minimal changes in a 10-year clinical trial. J Neurol Sci 255:57–63CrossRefPubMed
57.
Rao SM, Martin AL, Huelin R, Wissinger E, Khankhel Z, Kim E et al (2014) Correlations between MRI and information processing speed in ms: a meta-analysis. Mult Scler Int 2014:975803PubMedPubMedCentral
58.
Kirk J, Plumb J, Mirakhur M, McQuaid S (2003) Tight junctional abnormality in multiple sclerosis white matter affects all calibres of vessel and is associated with blood-brain barrier leakage and active demyelination. J Pathol 201:319–327CrossRefPubMed
59.
Floris S, Blezer EL, Schreibelt G, Dopp E, van der Pol SM, Schadee-Eestermans IL et al (2004) Blood-brain barrier permeability and monocyte infiltration in experimental allergic encephalomyelitis: a quantitative MRI study. Brain 127:616–627CrossRefPubMed
60.
Silver NC, Tofts PS, Symms MR, Barker GJ, Thompson AJ, Miller DH (2001) Quantitative contrast-enhanced magnetic resonance imaging to evaluate blood-brain barrier integrity in multiple sclerosis: a preliminary study. Mult Scler 7:75–82CrossRefPubMed
61.
Inglese M, Mancardi GL, Pagani E, Rocca MA, Murialdo A, Saccardi R et al (2004) Brain tissue loss occurs after suppression of enhancement in patients with multiple sclerosis treated with autologous haematopoietic stem cell transplantation. J Neurol Neurosurg Psychiatry 75:643–644PubMedPubMedCentral
62.
Inglese M, Benedetti B, Filippi M (2005) The relation between MRI measures of inflammation and neurodegeneration in multiple sclerosis. J Neurol Sci 233:15–19CrossRefPubMed
63.
Kanda T, Ishii K, Kawaguchi H, Kitajima K, Takenaka D (2014) 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 270:834–841CrossRefPubMed
64.
McDonald RJ, McDonald JS, Kallmes DF, Jentoft ME, Murray DL, Thielen KR et al (2015) Intracranial gadolinium deposition after contrast-enhanced mr imaging. Radiology 275:772–782CrossRefPubMed
65.
Fischer JS (2001) Cognitive impairment in multiple sclerosis. In: Cook SD (ed) Handbook of multiple sclerosis, 3rd edn. Marcel Dekker, Inc., New York, pp 233–256
66.
Kennedy MR, Wozniak JR, Muetzel RL, Mueller BA, Chiou HH, Pantekoek K et al (2009) White matter and neurocognitive changes in adults with chronic traumatic brain injury. J Int Neuropsychol Soc 15:130–136CrossRefPubMedPubMedCentral
Metadata
Title
Normal appearing white matter permeability: a marker of inflammation and information processing speed deficit among relapsing remitting multiple sclerosis patients
Authors
Eldar Eftekhari
Seyed-Parsa Hojjat
Rita Vitorino
Timothy J. Carroll
Charles Grady Cantrell
Liesly Lee
Matthew W. Taylor
Sarah A. Morrow
Haddas Benhabib
Richard I. Aviv
Andrea Kassner
Publication date
01-08-2017
Publisher
Springer Berlin Heidelberg
Published in
Neuroradiology / Issue 8/2017
Print ISSN: 0028-3940
Electronic ISSN: 1432-1920
DOI
https://doi.org/10.1007/s00234-017-1862-7

Other articles of this Issue 8/2017

Neuroradiology 8/2017 Go to the issue

Diagnostic Neuroradiology

Subject-specific regional measures of water diffusion are associated with impairment in chronic spinal cord injury

Erratum

Erratum to: Training guidelines for endovascular stroke intervention: an international multi-society consensus document

Interventional Neuroradiology

Fluid-attenuated inversion recovery vascular hyperintensities in predicting cerebral hyperperfusion after intracranial arterial stenting

Diagnostic Neuroradiology

Cost-effectiveness analysis of a non-contrast screening MRI protocol for vestibular schwannoma in patients with asymmetric sensorineural hearing loss

Paediatric Neuroradiology

Extended diffusion weighted magnetic resonance imaging with two-compartment and anomalous diffusion models for differentiation of low-grade and high-grade brain tumors in pediatric patients

Diagnostic Neuroradiology

Role of coronal high-resolution diffusion-weighted imaging in acute optic neuritis: a comparison with axial orientation