Abstract
Purpose
Multiple sclerosis (MS) is a disease that progresses not only with demyelination but also with neurodegeneration. One of the goals of drug treatment in MS is to prevent neurodegeneration. Cortical thickness (CT), sulcal depth (SD), and local gyrification index (LGI) are indicators related to neurodegeneration. The aim of this study is to investigate changes in CT, SD, and LGI in patients with relapsing-remitting MS (RRMS).
Methods
T1 images of 74 RRMS patients and 65 healthy controls were used. T1 hypointense areas in RRMS patients were corrected using fully automated methods. CT, SD, and LGI were calculated for each patient.
Results
RRMS patients showed widespread cortical thinning, especially in bilateral temporoparietal areas, decreased SD in bilateral supramarginal gyrus, superior temporal gyrus, postcentral gyrus, and transverse temporal gyrus, and decreased LGI, especially in the left posterior cingulate gyrus and insula. The decrease in cortical thickness was associated with the number of attacks and lesion volume. EDSS was related to CT in the right lingual, inferior temporal, and fusiform gyrus. The LGI was correlated with T2 lesion volume in bilateral insula, with EDSS in the right insula and transverse and superior temporal gyri, and with the number of attacks in the right paracentral gyrus and pre-cuneus. However, SD did not show any correlation with EDSS, T2 lesion volume, or the number of attacks.
Conclusion
Our results demonstrate widespread cortical thinning, decreased sulcal depth in local areas, and decreased gyrification in folds in RRMS patients, which are related to clinical parameters.
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References
Klaver R, De Vries HE, Schenk GJ, Geurts JJG (2013) Grey matter damage in multiple sclerosis: a pathology perspective. Prion 7:66–75. https://doi.org/10.4161/pri.23499
Kappos L, De Stefano N, Freedman MS et al (2016) Inclusion of brain volume loss in a revised measure of “no evidence of disease activity” (NEDA-4) in relapsing-remitting multiple sclerosis. Mult Scler 22(10):1297–1305. https://doi.org/10.1177/1352458515616701
Mesaros S, Rovaris M, Pagani E et al (2008) A magnetic resonance imaging voxel-based morphometry study of regional gray matter atrophy in patients with benign multiple sclerosis. Arch Neurol 65(9):1223–1230. https://doi.org/10.1001/archneur.65.9.1223
Goto M, Abe O, Hagiwara A et al (2022) Advantages of using both voxel-and surface-based morphometry in cortical morphology analysis: a review of various applications. Magn Reson Med Sci 21(1):41–57. https://doi.org/10.2463/mrms.rev.2021-0096
Narayana PA, Govindarajan KA, Goel P et al (2013) Regional cortical thickness in relapsing remitting multiple sclerosis: a multi-center study. Neuroimage Clin 2(1):120–131. https://doi.org/10.1016/j.nicl.2012.11.009
Baghdadi M, Badwey ME, Khalil M, Dawoud RM (2022) Brain magnetic resonance imaging surface-based analysis and cortical thickness measurement in relapsing remission multiple sclerosis. Egypt J Radiol Nucl Med 53(1). https://doi.org/10.1186/s43055-021-00686-9
Stellmann JP, Wanke N, Maarouf A et al (2021) Cognitive performance shows domain specific associations with regional cortical thickness in multiple sclerosis. Neuroimage Clin 30:102606. https://doi.org/10.1016/j.nicl.2021.102606
Tsagkas C, Chakravarty MM, Gaetano L et al (2020) Longitudinal patterns of cortical thinning in multiple sclerosis. Hum Brain Mapp 41(8):2198–2215. https://doi.org/10.1002/hbm.24940
Jin K, Zhang T, Shaw M, Sachdev P, Cherbuin N (2018) Relationship between sulcal characteristics and brain aging. Front Aging Neurosci 10:339. https://doi.org/10.3389/fnagi.2018.00339
Cai K, Xu H, Guan H et al (2017) Identification of early-stage Alzheimer’s disease using sulcal morphology and other common neuroimaging indices. PloS One 12(1):e0170875. https://doi.org/10.1371/journal.pone.0170875
Li M, Hua K, Li S et al (2019) Cortical morphology of chronic users of codeine-containing cough syrups: association with sulcal depth, gyrification, and cortical thickness. Eur Radiol 29(11):5901–5909. https://doi.org/10.1007/s00330-019-06165-0
Libero LE, Schaer M, Li DD, Amaral DG, Nordahl CW (2019) A longitudinal study of local gyrification ındex in young boys with autism spectrum disorder. Cereb Cortex 29(6):2575–2587. https://doi.org/10.1093/cercor/bhy126
Long J, Xu J, Wang X et al (2020) Altered local gyrification ındex and corresponding functional connectivity in medication free major depressive disorder. Front Psychiatry 11:585401. https://doi.org/10.3389/fpsyt.2020.585401
Li M, Yan J, Wen H et al (2021) Cortical thickness, gyrification and sulcal depth in trigeminal neuralgia. Sci Rep 11(1):16322. https://doi.org/10.1038/s41598-021-95811-z
Joy A, Nagarajan R, Daar ES et al (2023) Alterations of gray and white matter volumes and cortical thickness in treated HIV-positive patients. Magn Reson Imaging 95:27–38. https://doi.org/10.1016/j.mri.2022.10.006
Cuschieri S (2019) The STROBE guidelines. Saudi J Anaesth 13(5):S31–S34. https://doi.org/10.4103/sja.SJA_543_18
Thompson AJ, Banwell BL, Barkhof F et al (2018) Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 17(2):162–173. https://doi.org/10.1016/S1474-4422(17)30470-2
Schmidt P, Gaser C, Arsic M et al (2012) An automated tool for detection of FLAIR-hyperintense white-matter lesions in multiple sclerosis. Neuroimage. 59(4):3774–3783. https://doi.org/10.1016/j.neuroimage.2011.11.032
Gaser C, Dahnke R, Thompson PM, Kurth F, Luders E, Alzheimer’s Disease Neuroimaging Initiative Title of the paper: CAT-a computational anatomy toolbox for the analysis of structural MRI data. https://doi.org/10.1101/2022.06.11.495736
Luders E, Thompson PM, Narr KL, Toga AW, Jancke L, Gaser C (2006) A curvature-based approach to estimate local gyrification on the cortical surface. Neuroimage. 29(4):1224–1230. https://doi.org/10.1016/j.neuroimage.2005.08.049
Luders E, Thompson PM, Narr KL, Toga AW, Jancke L, Gaser C (2006) A curvature-based approach to estimate local gyrification on the cortical surface. Neuroimage. 29(4):1224–1230. https://doi.org/10.1016/j.neuroimage.2005.08.049
Nicastro N, Malpetti M, Cope TE et al (2020) Cortical complexity analyses and their cognitive correlate in Alzheimer’s disease and frontotemporal dementia. J Alzheimers Dis 76(1):331–340. https://doi.org/10.3233/JAD-200246
Im K, Lee JM, Won Seo S, Hyung Kim S, Kim SI, Na DL (2008) Sulcal morphology changes and their relationship with cortical thickness and gyral white matter volume in mild cognitive impairment and Alzheimer’s disease. Neuroimage. 43(1):103–113. https://doi.org/10.1016/j.neuroimage.2008.07.016
Wang JY, Danial M, Soleymanzadeh C et al (2020) Cortical gyrification and its relationships with molecular measures and cognition in children with the FMR1 premutation. Sci Rep 10(1):16059. https://doi.org/10.1038/s41598-020-73040-0
Kelly PA, Viding E, Wallace GL et al (2013) Cortical thickness, surface area, and gyrification abnormalities in children exposed to maltreatment: neural markers of vulnerability? Biol Psychiatry 74(11):845–852. https://doi.org/10.1016/j.biopsych.2013.06.020
Chen QF, Zhang XH, Zou TX, Huang NX, Chen HJ (2020) Reduced cortical complexity in cirrhotic patients with minimal hepatic encephalopathy. Neural Plast 2020:7364649. https://doi.org/10.1155/2020/7364649
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Genç, B., Aslan, K., Şen, S. et al. Cortical morphological changes in multiple sclerosis patients: a study of cortical thickness, sulcal depth, and local gyrification index. Neuroradiology 65, 1405–1413 (2023). https://doi.org/10.1007/s00234-023-03185-y
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DOI: https://doi.org/10.1007/s00234-023-03185-y