Hippocampal microstructural damage correlates with memory impairment in clinically isolated syndrome suggestive of multiple sclerosis
Abstract
Objective:
We investigated whether diffusion tensor imaging (DTI) could reveal early hippocampal damage and clinically relevant correlates of memory impairment in persons with clinically isolated syndrome (CIS) suggestive of multiple sclerosis (MS).
Methods:
A total of 37 persons with CIS, 32 with MS and 36 controls prospectively included from 2011 to 2014 were tested for cognitive performances and scanned with 3T-magnetic resonance imaging (MRI) to assess volumetric and DTI changes within the hippocampus, whole brain volume and T2-lesion load.
Results:
While there was no hippocampal atrophy in the CIS group, hippocampal fractional anisotropy (FA) was significantly decreased compared to controls. Decrease in hippocampal FA together with increased mean diffusivity (MD) was even more prominent in MS patients. In CIS, hippocampal MD was correlated with episodic verbal memory performance (r = −0.57, p = 0.0002 and odds ratio (OR) = 0.058, 95% confidence interval (CI) = 0.0057–0.59, p = 0.016 adjusted for age, gender, depression and T2-lesion load), but not with cognitive tasks unrelated to hippocampal functions. Hippocampal MD was the only variable discriminating memory-impaired from memory-preserved persons with CIS (area under the curve (AUC) = 0.77, sensitivity = 90.0%, specificity = 70.3%, positive predictive value (PPV) = 52.9%, negative predictive value (NPV) = 95.0%).
Conclusion:
DTI alterations within the hippocampus might reflect early neurodegenerative processes that are correlated with episodic memory performance, discriminating persons with CIS according to their memory status.
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References
1. Chiaravalloti ND, DeLuca J. Cognitive impairment in multiple sclerosis. Lancet Neurol 2008; 7(12): 1139–1151.
2. Rocca MA, Amato MP, De Stefano N, et al. Clinical and imaging assessment of cognitive dysfunction in multiple sclerosis. Lancet Neurol 2015; 14(3): 302–317.
3. Ruet A, Deloire M, Hamel D, et al. Cognitive impairment, health-related quality of life and vocational status at early stages of multiple sclerosis: A 7-year longitudinal study. J Neurol 2013; 260(3): 776–784.
4. Dineen RA, Vilisaar J, Hlinka J, et al. Disconnection as a mechanism for cognitive dysfunction in multiple sclerosis. Brain 2009; 132(Pt 1): 239–249.
5. Sicotte NL, Kern KC, Giesser BS, et al. Regional hippocampal atrophy in multiple sclerosis. Brain 2008; 131(Pt 4): 1134–1141.
6. Benedict RHB, Ramasamy D, Munschauer F, et al. Memory impairment in multiple sclerosis: Correlation with deep grey matter and mesial temporal atrophy. J Neurol Neurosurg Psychiatry 2009; 80(2): 201–206.
7. Longoni G, Rocca MA, Pagani E, et al. Deficits in memory and visuospatial learning correlate with regional hippocampal atrophy in MS. Brain Struct Funct 2015; 220(1): 435–444.
8. Koenig KA, Sakaie KE, Lowe MJ, et al. Hippocampal volume is related to cognitive decline and fornicial diffusion measures in multiple sclerosis. Magn Reson Imaging 2014; 32(4): 354–358.
9. Achiron A, Barak Y. Cognitive impairment in probable multiple sclerosis. J Neurol Neurosurg Psychiatry 2003; 74(4): 443–446.
10. Feuillet L, Reuter F, Audoin B, et al. Early cognitive impairment in patients with clinically isolated syndrome suggestive of multiple sclerosis. Mult Scler 2007; 13(1): 124–127.
11. Henry RG, Shieh M, Okuda DT, et al. Regional grey matter atrophy in clinically isolated syndromes at presentation. J Neurol Neurosurg Psychiatry 2008; 79(11): 1236–1244.
12. Rocca MA, Preziosa P, Mesaros S, et al. Clinically isolated syndrome suggestive of multiple sclerosis: Dynamic patterns of gray and white matter changes-a 2-year MR imaging study. Radiology 2016; 278(3): 841–853.
13. Calabrese M, Rinaldi F, Mattisi I, et al. The predictive value of gray matter atrophy in clinically isolated syndromes. Neurology 2011; 77(3): 257–263.
14. Audoin B, Zaaraoui W, Reuter F, et al. Atrophy mainly affects the limbic system and the deep grey matter at the first stage of multiple sclerosis. J Neurol Neurosurg Psychiatry 2010; 81(6): 690–695.
15. Bergsland N, Horakova D, Dwyer MG, et al. Subcortical and cortical gray matter atrophy in a large sample of patients with clinically isolated syndrome and early relapsing-remitting multiple sclerosis. AJNR: Am J Neuroradiol 2012; 33(8): 1573–1578.
16. Preziosa P, Rocca MA, Mesaros S, et al. Intrinsic damage to the major white matter tracts in patients with different clinical phenotypes of multiple sclerosis: A voxelwise diffusion-tensor MR study. Radiology 2011; 260(2): 541–550.
17. Cappellani R, Bergsland N, Weinstock-Guttman B, et al. Diffusion tensor MRI alterations of subcortical deep gray matter in clinically isolated syndrome. J Neurol Sci 2014; 338(1–2): 128–134.
18. Deppe M, Krämer J, Tenberge J-G, et al. Early silent microstructural degeneration and atrophy of the thalamocortical network in multiple sclerosis. Hum Brain Mapp 2016; 37: 1866–1879.
19. Douaud G, Menke RAL, Gass A, et al. Brain microstructure reveals early abnormalities more than two years prior to clinical progression from mild cognitive impairment to Alzheimer’s disease. J Neurosci 2013; 33(5): 2147–2155.
20. Polman CH, Reingold SC, Edan G, et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the ‘McDonald criteria’. Ann Neurol 2005; 58(6): 840–846.
21. Boringa JB, Lazeron RH, Reuling IE, et al. The brief repeatable battery of neuropsychological tests: normative values allow application in multiple sclerosis clinical practice. Mult Scler 2001; 7(4): 263–267.
22. Benedict RHB, Zivadinov R. Reliability and validity of neuropsychological screening and assessment strategies in MS. J Neurol 2007; 254 (Suppl. 2): 1122–1125.
23. Van Leemput K, Maes F, Vandermeulen D, et al. Automated segmentation of multiple sclerosis lesions by model outlier detection. IEEE Trans Med Imaging 2001; 20(8): 677–688.
24. Manjón JV, Coupé P, Martí-Bonmatí L, et al. Adaptive non-local means denoising of MR images with spatially varying noise levels. J Magn Reson Imaging 2010; 31(1): 192–203.
25. Avants BB, Tustison NJ, Song G, et al. A reproducible evaluation of ANTs similarity metric performance in brain image registration. NeuroImage 2011; 54(3): 2033–2044.
26. Coupé P, Manjón JV, Fonov V, et al. Patch-based segmentation using expert priors: Application to hippocampus and ventricle segmentation. NeuroImage 2011; 54(2): 940–954.
27. Frisoni GB, Jack CR, Bocchetta M, et al. The EADC-ADNI harmonized protocol for manual hippocampal segmentation on magnetic resonance: Evidence of validity. Alzheimer’s Dement 2015; 11(2): 111–125.
28. Manjón JV, Coupé P, Concha L, et al. Diffusion weighted image denoising using overcomplete local PCA. PLoS ONE 2013; 8(9):e73021.
29. Leszczynski M. How does hippocampus contribute to working memory processing? Front Hum Neurosci 2011; 5: 168.
30. Dutta R, Chang A, Doud MK, et al. Demyelination causes synaptic alterations in hippocampi from multiple sclerosis patients. Ann Neurol 2011; 69(3): 445–454.
31. Benedict RHB, Zivadinov R. Risk factors for and management of cognitive dysfunction in multiple sclerosis. Nat Rev Neurol 2011; 7(6): 332–342.
32. Daams M, Steenwijk MD, Schoonheim MM, et al. Multi-parametric structural magnetic resonance imaging in relation to cognitive dysfunction in long-standing multiple sclerosis. Mult Scler 2016; 22(5): 608–619.
33. Preziosa P, Rocca MA, Pagani E, et al. Structural MRI correlates of cognitive impairment in patients with multiple sclerosis: A multicenter study. Hum Brain Mapp 2016; 37(4): 1627–1644.
34. Strober L, Englert J, Munschauer F, et al. Sensitivity of conventional memory tests in multiple sclerosis: Comparing the Rao brief repeatable neuropsychological battery and the minimal assessment of cognitive function in MS. Mult Scler 2009; 15(9): 1077–1084.
35. Calabrese M, Battaglini M, Giorgio A, et al. Imaging distribution and frequency of cortical lesions in patients with multiple sclerosis. Neurology 2010; 75(14): 1234–1240.
36. Hulst HE, Schoonheim MM, Van Geest Q, et al. Memory impairment in multiple sclerosis: Relevance of hippocampal activation and hippocampal connectivity. Mult Scler 2015; 21: 1705–1712.
37. Hagemeier J, Weinstock-Guttman B, Bergsland N, et al. Iron deposition on SWI-filtered phase in the subcortical deep gray matter of patients with clinically isolated syndrome may precede structure-specific atrophy. AJNR: Am J Neuroradiol 2012; 33(8): 1596–1601.
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Article first published online: October 25, 2016
Issue published: August 2017
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PubMed: 27780913
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