Clinical Research
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Evaluation of the correlation between thalamic area and cognitive functions in patients with early-stage relapsing-remitting multiple sclerosis

Year 2023, Volume: 6 Issue: 2, 280 - 289, 31.08.2023

Selahattin Ayas , Sibel Canbaz Kabay

https://doi.org/10.36516/jocass.1333415

Abstract

Background: The aim of this study is to investigate the presence of cognitive dysfunction and deep gray matter involvement in the early-stages of Relapsing-Remitting Multiple Sclerosis(RRMS) disease and examine the relationship between them.
Materials and Methods: Thirty-four patients and 23 healthy individuals were included in the study. Patients diagnosed with RRMS according to the Revised 2010 and 2017 McDonald criteria, aged between 18-50, were enrolled in the study. The control group consisted of 23 healthy individuals with normal neurological examination, cranial magnetic resonance imaging(MRI), and cognitive functions. All participants underwent a neuropsychological test battery that covers memory, executive functions, language, and visuospatial domains, and the results of these tests were compared among the study groups. The data on MRI parameters, including the areas of the thalamus and corpus callosum as well as the width of the third ventricle, were compared among the study groups. Finally, the relationship between neuropsychological test results and MRI parameters was investigated in patients with early-stage RRMS.
Results: The mean duration of the disease for MS patients was 3.53 years, and their median EDSS score was 2. It was observed that memory, executive functions, and fine motor skills were affected in early-stage RRMS patients. This impairment correlated with a decrease in the thalamus and corpus callosum areas and an increase in the third ventricle width.
Conclusion: The MRI parameters defined as biomarkers for potential cognitive impairments in RRMS have critical importance in predicting the prognosis of the disease and taking early measures against future cognitive dysfunction.

Keywords

Multiple Sclerosis deep gray matter thalamus cognitive dysfunction

References

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Erken Evre Relapsing-Remitting Multipl Skleroz Hastalarında Talamus Alanı ile Bilişsel İşlevler Arasındaki İlişkinin Değerlendirilmesi

Year 2023, Volume: 6 Issue: 2, 280 - 289, 31.08.2023

Selahattin Ayas , Sibel Canbaz Kabay

https://doi.org/10.36516/jocass.1333415

Abstract

Amaç: Bu çalışmanın amacı, Relapsing-Remitting Multiple Skleroz (RRMS) hastalığının erken evrelerinde bilişsel işlev bozukluğunun ve derin gri madde tutulumunun varlığını araştırmak ve aralarındaki ilişkiyi incelemektir.
Materyal ve Metot: Çalışmaya 34 hasta ve 23 sağlıklı birey dahil edildi. Çalışmaya, 2010 ve 2017 Revize McDonald kriterlerine göre RRMS tanısı konulan, 18-50 yaş arasındaki hastalar alındı. Kontrol grubu ise normal nörolojik muayene, kraniyal manyetik rezonans görüntüleme (MRG) ve bilişsel fonksiyonları olan 23 sağlıklı bireyden oluşuyordu. Tüm katılımcılara bellek, yürütücü işlevler, dil ve görsel-mekansal alan işlevlerini kapsayan bir nöropsikolojik test bataryası uygulandı ve bu testlerin sonuçları çalışma grupları arasında karşılaştırıldı. Talamus ve korpus kallozum alanları ile üçüncü ventrikül genişliği de dahil olmak üzere MRG parametrelerine ilişkin veriler, çalışma grupları arasında karşılaştırıldı. Son olarak, erken evre RRMS'li hastalarda nöropsikolojik test sonuçları ile MRG parametreleri arasındaki ilişki araştırıldı.
Bulgular: MS hastalarının ortalama hastalık süresi 3.53 yıl ve ortanca EDSS skoru 2 idi. Erken evre RRMS hastalarında bellek, yürütücü işlevler ve ince motor becerilerin etkilendiği gözlendi. Bu bozulma, talamus ve korpus kallozum alanlarında azalma ve üçüncü ventrikül genişliğindeki artış ile koreleydi.
Sonuç: RRMS'de potansiyel bilişsel bozukluklar için biyobelirteç olarak tanımlanan MRG parametreleri, hastalığın prognozunu tahmin etmede ve gelecekteki bilişsel işlev bozukluklarına karşı erken önlemler alınmasında kritik öneme sahiptir.

Keywords

Multiple Skleroz derin gri madde talamus bilişsel işlev bozukluğu

References

  • 1.Altıntas A. Multipl Sklerozun immunopatogenezi ve patolojisi. Türkiye Klinikleri J Neurol-Special Topics. 2009;2(2): 1-8.
  • 2.Belbasis L, Bellou V, Evangelou E, et al. Environmental risk factors and mul¬tiple sclerosis: an umbrella review of systematic reviews and meta-analyses. Lancet Neurol. 2015; 14(3): 263-73. https://doi.org/10.1016/S1474-4422(14)70267-4
  • 3.Mollison D, Sellar R, Bastin M, et al. The clinico-radiological paradox of cog¬nitive function and MRI burden of white matter lesions in people with mul¬tiple sclerosis: A systematic review and meta-analysis. PLoS One. 2017; 12(5). https://doi.org/10.1371/journal.pone.0177727
  • 4.Dutta R, Trapp BD. Mechanisms of neuronal dysfunction and degeneration in multiple sclerosis. Prog Neurobiol. 2011; 93(1): 1-12. https://doi.org/10.1016/j.pneurobio.2010.09.005
  • 5.Langdon DW. Cognition in multiple sclerosis. Curr Opin Neurol. 2011;24(3):244-9. https://doi.org/10.1097/WCO.0b013e328346a43b
  • 6.Ghaffar O, Feinstein A. The neuropsychiatry of multiple sclerosis: a review of recent developments. Curr Opin Psychiatry. 2007; (3): 278-85. https://doi.org/10.1097/YCO.0b013e3280eb10d7
  • 7.Amato MP, Zipoli V, Portaccio E. Cognitive changes in multiple sclerosis. Expert Rev Neurother. 2008; 8(10): 1585-96. https://doi.org/10.1586/14737175.8.10.1585
  • 8.Achiron A, Chapman J, Magalashvili D, et al. Modeling of cognitive impair¬ment by disease duration in multiple sclerosis: a cross-sectional study. PLoS One. 2013; 8(8). https://doi.org/10.1371/journal.pone.0071058
  • 9.Amato MP, Zipoli V, Goretti B, et al. Benign multiple sclerosis: cognitive, psychological and social aspects in a clinical cohort. J Neurol. 2006; 253(8): 1054-9. https://doi.org/10.1007/s00415-006-0161-8
  • 10.Lucchinetti CF, Popescu BFG, Bunyan RF, et al. Inflammatory cortical de¬myelination in early multiple sclerosis. N Engl J Med. 2011; 365(23): 2188-97. https://doi.org/10.1056/NEJMoa1100648
  • 11.Gh Popescu BF, Lucchinetti CF. Meningeal and cortical grey matter pathol¬ogy in multiple sclerosis. BMC Neurol. 2012; 12: 11. https://doi.org/10.1186/1471-2377-12-11
  • 12.Hulst HE, Geurts JJG. Gray matter imaging in multiple sclerosis: what have we learned? BMC Neurol. 2011; 11: 153. https://doi.org/10.1186/1471-2377-11-153
  • 13.Child ND, Benarroch EE. Anterior nucleus of the thalamus: functional or¬ganization and clinical implications. Neurology. 2013; 81(21): 1869- 76. https://doi.org/10.1212/01.wnl.0000436078.95856.56
  • 14.Minagar A, Barnett MH, Benedict RHB, et al. The thalamus and multiple sclerosis: modern views on pathologic, imaging, and clinical aspects. Neurol¬ogy. 2013; 80(2): 210-9. https://doi.org/10.1212/WNL.0b013e31827b910b
  • 15.Aggleton JP, Sahgal A. The contribution of the anterior thalamic nuclei to anterograde amnesia. Neuropsychologia. 1993; 31(10): 1001-19. https://doi.org/10.1016/0028-3932(93)90029-Y
  • 16.Kern KC, Gold SM, Lee B, et al. Thalamic-hippocampal-prefrontal disrup¬tion in relapsing-remitting multiple sclerosis. NeuroImage Clin. 2014; 8: 440-7. https://doi.org/10.1016/j.nicl.2014.12.015
  • 17.Richter P, Werner J, Heerlein A, et al. On the validity of the Beck Depres¬sion Inventory. A review. Psychopathology. 1998; 31(3): 160-8. https://doi.org/10.1159/000066239
  • 18.Oktem O. A verbal test of memory processes: a preliminary study. Arch Neuropsychatry. 1992; 29: 196-206.
  • 19.Filippi M, Rocca MA. MRI and cognition in multiple sclerosis. Neurol Sci. 2010; 31(Suppl 2). https://doi.org/10.1007/s10072-010-0367-5
  • 20.Benedict RHB, Weinstock-Guttman B, Fishman I, et al. Prediction of neu¬ropsychological impairment in multiple sclerosis: comparison of conven¬tional magnetic resonance imaging measures of atrophy and lesion burden. Arch Neurol. 2004; 61(2): 226-30. https://doi.org/10.1001/archneur.61.2.226
  • 21.Müller M, Esser R, Kötter K, et al. Width of 3. Ventricle: reference values and clinical relevance in a cohort of patients with relapsing remitting multi¬ple sclerosis. Open Neurol J. 2013; 7(1): 11-6. https://doi.org/10.2174/1874205X01307010011
  • 22.Karakaş P, Koç Z, Koç F, et al. Morphometric MRI evaluation of corpus cal¬losum and ventricles in normal adults. Neurol Res. 2011; 33(10): 1044-9. https://doi.org/10.1179/1743132811Y.0000000030
  • 23.Honarmand K, Akbar N, Kou N, et al. Predicting employment status in multiple sclerosis patients: the utility of the MS functional composite. J Neu¬rol. 2011; 258(2): 244-9. https://doi.org/10.1007/s00415-010-5736-8
  • 24.Benedict RHB, Zivadinov R. Risk factors for and management of cognitive dysfunction in multiple sclerosis. Nat Rev Neurol. 2011; 7(6): 332-42. https://doi.org/10.1038/nrneurol.2011.61
  • 25.Glanz BI, Holland CM, Gauthier SA, et al. Cognitive dysfunction in patients with clinically isolated syndromes or newly diagnosed multiple sclerosis. Mult Scler. 2007; 13(8): 1004-10. https://doi.org/10.1177/1352458507077943
  • 26.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): 124-7. https://doi.org/10.1177/1352458506071196
  • 27.Johnen A, Landmeyer NC, Bürkner PC, et al. Distinct cognitive impair-ments in different disease courses of multiple sclerosis-A systematic review and meta-analysis. Neurosci Biobehav Rev. 2017; 83: 568-78. https://doi.org/10.1016/j.neubiorev.2017.09.005
  • 28.Amato MP, Bartolozzi ML, Zipoli V, et al. Neocortical volume decrease in relapsing-remitting MS patients with mild cognitive impairment. Neurology. 2004; 63(1): 89-93. https://doi.org/10.1212/01.WNL.0000129544.79539.D5
  • 29.Bagnato F, Salman Z, Kane R, et al. T1 cortical hypointensities and their association with cognitive disability in multiple sclerosis. Mult Scler. 2010; 16(10): 1203-12. https://doi.org/10.1177/1352458510377223
  • 30.Mesaros S, Rocca MA, Sormani MP, et al. Clinical and conventional MRI predictors of disability and brain atrophy accumulation in RRMS. A large scale, short-term follow-up study. J Neurol. 2008; 255(9): 1378-83. https://doi.org/10.1007/s00415-008-0924-5
  • 31.Starr JM, Lonie J. The influence of pre-morbid IQ on Mini-Mental State Ex¬amination score at time of dementia presentation. Int J Geriatr Psychiatry. 2007; 22(4): 382-4. https://doi.org/10.1002/gps.1668
  • 32.Benedict RHB, Morrow SA, Weinstock Guttman B, et al. Cognitive reserve moderates decline in information processing speed in multiple sclerosis pa¬tients. J Int Neuropsychol Soc. 2010; 16(5): 829-35. https://doi.org/10.1017/S1355617710000688
  • 33.Forn C, Belenguer A, Parcet-Ibars MA, et al. Information-processing speed is the primary deficit underlying the poor performance of multiple sclerosis patients in the Paced Auditory Serial Addition Test (PASAT). J Clin Exp Neu¬ropsychol. 2008; 30(7): 789-96. https://doi.org/10.1080/13803390701779560
  • 34.Locatelli L, Zivadinov R, Grop A, et al. Frontal parenchymal atrophy measures in multiple sclerosis. Mult Scler. 2004; 10(5): 562-8. https://doi.org/10.1191/1352458504ms1093oa
  • 35.Deloire MSA, Salort E, Bonnet M, et al. Cognitive impairment as marker of diffuse brain abnormalities in early relapsing remitting multiple sclerosis. J Neurol Neurosurg Psychiatry. 2005; 76(4): 519-26. https://doi.org/10.1136/jnnp.2004.045872
  • 36.Achiron A, Polliack M, Rao SM, et al. Cognitive patterns and progression in multiple sclerosis: construction and validation of percentile curves. J Neu¬rol Neurosurg Psychiatry. 2005; 76(5): 744-9. https://doi.org/10.1136/jnnp.2004.045518
  • 37.Batista S, Zivadinov R, Hoogs M, et al. Basal ganglia, thalamus and neocor¬tical atrophy predicting slowed cognitive processing in multiple sclerosis. J Neurol. 2012; 259(1): 139-46. https://doi.org/10.1007/s00415-011-6147-1
  • 38.Barak Y, Lavie M, Achiron A. Screening for early cognitive impairment in multiple sclerosis patients using the clock drawing test. J Clin Neurosci. 2002; 9(6): 629-32. https://doi.org/10.1054/jocn.2002.1110
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There are 55 citations in total.

Details

Primary Language English
Subjects Clinical Sciences (Other)
Journal Section Articles
Authors

Selahattin Ayas 0000-0001-9841-353X

Sibel Canbaz Kabay 0000-0003-4808-2191

Publication Date August 31, 2023
Acceptance Date August 22, 2023
Published in Issue Year 2023 Volume: 6 Issue: 2

Cite

APA Ayas, S., & Canbaz Kabay, S. (2023). Evaluation of the correlation between thalamic area and cognitive functions in patients with early-stage relapsing-remitting multiple sclerosis. Journal of Cukurova Anesthesia and Surgical Sciences, 6(2), 280-289. https://doi.org/10.36516/jocass.1333415
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