Predictors and integrative index of severity of cognitive disorders in cerebral microangiopathy

Dobrynina LA, Gadzhieva ZS, Shamtieva KV, et al. Predictors and integrative index of severity of cognitive disorders in cerebral microangiopathy. S.S. Korsakov Journal of Neurology and Psychiatry. 2022;122(4):52‑60. (In Russ.)
https://doi.org/10.17116/jnevro202212204152

Подписка 2026 Журнал неврологии и психиатрии им. С.С. Корсакова (S.S. Korsakov Journal of Neurology and Psychiatry)

Использование инфографики авторами научных работ

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OBJECTIVE

To search for sensitive predictors of cognitive impairment (CI) and an integrative index of their severity.

MATERIAL AND METHODS

We assessed CI and diffusion-tensor MRI (DT-MRI) in the regions of interest (ROI) significant for CI in 74 patients (48 women, mean age 60.6±6.9 years) with cerebral small vessel disease (CSVD). The results of DT-MRI were used to construct a predictive model of CI using binary logistic regression and to calculate an integrative index of CI severity.

RESULTS

According to the constructed model, the predictors of CI were axial diffusivity (AD) of posterior frontal periventricular normal-appearing white matter (pvNAWM), right middle cingulum bundle (CB) and mid-posterior corpus callosum (CC). ROC analysis showed strong model predictive power for CI in cSVD (AUC (95% CI): 0.845 (0.740—0.950)). The threshold value of the AD predictors model for CI in cSVD was 0.53 (sensitivity 84%, specificity 76%). AD predictors of CI showed significant correlations with white matter hyperintensities volume and MoCA scores. The presence of CI as measured by neuropsychological testing and regression equation solution was corresponded to individual AD predictors of patients exceeding the CI model’s threshold.

CONCLUSION

Disturbances in the AD of pvNAWM, right middle CB and mid-posterior CC associated with axonal damage are a predominant factor in the development of CI in CSVD. The predictors of CI and the integrative index of CI severity calculated on their basis can potentially be used as a tool for assessing the severity of CI and the effectiveness of treatment, as well as in clarifying the interaction between vascular and degenerative pathology and in developing measures for the prevention of CI in patients with MRI signs of cSVD.

Keywords:

cerebral small vessel disease

diffusion tensor imaging

cognitive impairment

predictors of cognitive impairment

an integrative index of the cognitive impairment severity

Authors:

Dobrynina L.A.

Research Center of Neurology

ORCID: 0000-0001-9929-2725

Gadzhieva Z.S.

Research Center of Neurology

ORCID: 0000-0001-7498-4063

Shamtieva K.V.

Research Center of Neurology

ORCID: 0000-0002-6995-1352

Kremneva E.I.

Research Center of Neurology

ORCID: 0000-0001-9396-6063

Filatov A.S.

Research Center of Neurology

ORCID: 0000-0002-5706-6997

Bitsieva E.T.

Research Center of Neurology

ORCID: 0000-0003-1464-0722

Mirokova E.D.

Research Center of Neurology

Krotenkova M.V.

Research Center of Neurology

ORCID: 0000-0003-3820-4554

Received:

20.12.2021

Accepted:

17.01.2022

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References:

Gorelick PB, Scuteri A, Black SE, et al. Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the American Heart Association. American Stroke Association. Stroke. 2011;42(9):2672-2713. https://doi.org/10.1161/str.0b013e3182299496
Deramecourt V, Slade JY, Oakley AE, et al. Staging and natural history of cerebrovascular pathology in dementia. Neurology. 2012;78(14):1043-1050. https://doi.org/10.1212/wnl.0b013e31824e8e7f
Wardlaw JM, Smith C, Dichgans M. Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging. Lancet Neurol. 2013;12(5):483-497. https://doi.org/10.1016/s1474-4422(13)70060-7
Kalashnikova LA, Gulevskaya TS, Dobrynina LA. Actual problems of brain pathology in cerebral microangiopathy. Zhurnal Nevrologii i Psikhiatrii im. S.S. Korsakova. 2018;118(2):90-99. (In Russ.). https://doi.org/10.17116/jnevro20181182190-99
Putilina MV. Current concepts about small vessel disease. Zhurnal Nevrologii i Psikhiatrii im. S.S. Korsakova. 2019;119(11):65-73. (In Russ.). https://doi.org/10.17116/jnevro201911911165
Parfenov VA, Kulesh AA. Cerebrovascular disease with neurocognitive impairment. Zhurnal Nevrologii i Psikhiatrii im. S.S. Korsakova. 2021;121(9):121-130. (In Russ.). https://doi.org/10.17116/jnevro2021121091121
Wardlaw JM, Smith EE, Biessels GJ, et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol. 2013;12(8):822-838. https://doi.org/10.1016/s1474-4422(13)70124-8
Gnedovskaya EV, Dobrynina LA, Krotenkova MV, Sergeeva AN. MRI in the assessment of cerebral small vessel disease. Annals of Clinical and Experimental Neurology. 2018;12(1):61-68. (In Russ.). https://doi.org/10.25692/ACEN.2018.1.9
Smith EE, Biessels GJ, De Guio F, et al. Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration. Alzheimers Dement (Amst). 2019;11:191-204. https://doi.org/10.1016/j.dadm.2019.01.002
Schmidt R, Berghold A, Jokinen H, et al. White matter lesion progression in LADIS: frequency, clinical effects, and sample size calculations. Stroke. 2012;43(10):2643-2647. https://doi.org/10.1161/strokeaha.112.662593
Pasi M, van Uden IW, Tuladhar AM, et al. White Matter Microstructural Damage on Diffusion Tensor Imaging in Cerebral Small Vessel Disease: Clinical Consequences. Stroke. 2016;47(6):1679-1684. https://doi.org/10.1161/strokeaha.115.012065
Raja R, Rosenberg G, Caprihan A. Review of diffusion MRI studies in chronic white matter diseases. Neurosci Lett. 2019;694:198-207. https://doi.org/10.1016/j.neulet.2018.12.007
Gouw AA, Seewann A, van der Flier WM, et al. Heterogeneity of small vessel disease: a systematic review of MRI and histopathology correlations. J Neurol Neurosurg Psychiatry. 2011;82(2):126-135. https://doi.org/10.1136/jnnp.2009.204685
Kremneva EI, Maximov II, Dobrynina LA, Krotenkova MV. The assessment of cerebral white matter microstructure in cerebral small vessel disease based on the diffusion-weighted magnetic resonance imaging. Annals of Clinical and experimental Neurology. 2020;14(1):33-43. (In Russ.). https://doi.org/10.25692/ACEN.2020.1.4
Lawrence AJ, Brookes RL, Zeestraten EA, et al. Pattern and Rate of Cognitive Decline in Cerebral Small Vessel Disease: A Prospective Study. PLoS One. 2015;10(8):e0135523. https://doi.org/10.1371/journal.pone.0135523
Benjamin P, Zeestraten E, Lambert C, et al. Progression of MRI markers in cerebral small vessel disease: Sample size considerations for clinical trials. J Cereb Blood Flow Metab. 2016;36(1):228-240. https://doi.org/10.1038/jcbfm.2015.113
Pasi M, Salvadori E, Poggesi A, et al. White matter microstructural damage in small vessel disease is associated with Montreal cognitive assessment but not with mini mental state examination performances: vascular mild cognitive impairment Tuscany study. Stroke. 2015;46(1):262-264. https://doi.org/10.1161/STROKEAHA.114.007553
O’Sullivan M, Morris RG, Huckstep B, et al. Diffusion tensor MRI correlates with executive dysfunction in patients with ischaemic leukoaraiosis. J Neurol Neurosurg Psychiatry. 2004;75(3):441-447. https://doi.org/10.1136/jnnp.2003.014910
Nitkunan A, Barrick TR, Charlton RA, et al. Multimodal MRI in cerebral small vessel disease: its relationship with cognition and sensitivity to change over time. Stroke. 2008;39(7):1999-2005. https://doi.org/10.1161/STROKEAHA.107.507475
Tuladhar AM, van Norden AG, de Laat KF, et al. White matter integrity in small vessel disease is related to cognition. Neuroimage Clin. 2015;7:518-524. https://doi.org/10.1016/j.nicl.2015.02.003
Song SK, Sun SW, Ju WK, et al. Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage. 2003;20(3):1714-1722. https://doi.org/10.1016/j.neuroimage.2003.07.005
Winklewski PJ, Sabisz A, Naumczyk P, et al. Understanding the Physiopathology Behind Axial and Radial Diffusivity Changes-What Do We Know? Front Neurol. 2018;9:92. https://doi.org/10.3389/fneur.2018.00092
Lawrence AJ, Patel B, Morris RG, et al. Mechanisms of cognitive impairment in cerebral small vessel disease: multimodal MRI results from the St George’s cognition and neuroimaging in stroke (SCANS) study. PLoS One. 2013;8(4):e61014. https://doi.org/10.1371/journal.pone.0061014
Williams OA, Zeestraten EA, Benjamin P, et al. Diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to cognitive change. Neuroimage Clin. 2017;16:330-342. https://doi.org/10.1016/j.nicl.2017.08.016
Williams OA, Zeestraten EA, Benjamin P, et al. Predicting Dementia in Cerebral Small Vessel Disease Using an Automatic Diffusion Tensor Image Segmentation Technique. Stroke. 2019;50(10):2775-2782. https://doi.org/10.1161/strokeaha.119.025843
Reed BR, Mungas DM, Kramer JH, et al. Profiles of neuropsychological impairment in autopsy-defined Alzheimer’s disease and cerebrovascular disease. Brain. 2007;130(Pt 3):731-739. https://doi.org/10.1093/brain/awl385
Vasquez BP, Zakzanis KK. The neuropsychological profile of vascular cognitive impairment not demented: a meta-analysis. J Neuropsychol. 2015;9(1):109-136. https://doi.org/10.1111/jnp.12039
Dobrynina LA, Gadzhieva ZSh, Kalashnikova LA, et al. Neuropsychological profile and vascular risk factors in patients with cerebral microangiopathy. Annals of Clinical and Experimental Neurology. 2018;12(4):5-15. (In Russ.). https://doi.org/10.25692/ACEN.2018.4.1
Shim YS, Yang DW, Roe CM, et al. Pathological correlates of white matter hyperintensities on magnetic resonance imaging. Dement Geriatr Cogn Disord. 2015;39(1-2):92-104. https://doi.org/10.1159/000366411
Kim KW, MacFall JR, Payne ME. Classification of white matter lesions on magnetic resonance imaging in elderly persons. Biol Psychiatry. 2008;64(4):273-280. https://doi.org/10.1016/j.biopsych.2008.03.024
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition: DSM-5. American Psychiatric Association, Arlington (USA): American Psychiatric Publishing; 2013.
Albert MS, DeKosky ST, Dickson D, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):270-279. https://doi.org/10.1016/j.jalz.2011.03.008
Whelton PK, Carey RM, Aronow WS, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2018;138(17):426-483. https://doi.org/10.1161/CIR.0000000000000597
Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695-699. https://doi.org/10.1111/j.1532-5415.2005.53221.x
Nosarti C, Rushe TM, Woodruff PW, et al. Corpus callosum size and very preterm birth: relationship to neuropsychological outcome. Brain. 2004;127(Pt 9):2080-2089. https://doi.org/10.1093/brain/awh230
Concha L, Gross DW, Beaulieu C. Diffusion tensor tractography of the limbic system. AJNR Am J Neuroradiol. 2005;26(9):2267-2274.
Schmidt P, Wink L. LST: A lesion segmentation tool for SPM. Manual/Documentation for Version 3.0.0 October 2019.
Liu X, Cheng R, Chen L, et al. Alterations of White Matter Integrity in Subcortical Ischemic Vascular Disease with and Without Cognitive Impairment: a TBSS Study. J Mol Neurosci. 2019;67(4):595-603. https://doi.org/10.1007/s12031-019-01266-3
Abraham HM, Wolfson L, Moscufo N, et al. Cardiovascular risk factors and small vessel disease of the brain: Blood pressure, white matter lesions, and functional decline in older persons. J Cereb Blood Flow Metab. 2016;36(1):132-142. https://doi.org/10.1038/jcbfm.2015.121
Kazumata K, Tha KK, Narita H, et al. Characteristics of Diffusional Kurtosis in Chronic Ischemia of Adult Moyamoya Disease: Comparing Diffusional Kurtosis and Diffusion Tensor Imaging. AJNR Am J Neuroradiol. 2016;37(8):1432-1439. https://doi.org/10.3174/ajnr.A4728
Yamanouchi H, Sugiura S, Shimada H. Loss of nerve fibres in the corpus callosum of progressive subcortical vascular encephalopathy. J Neurol. 1990;237(1):39-41. https://doi.org/10.1007/bf00319666
Aung WY, Mar S, Benzinger TL. Diffusion tensor MRI as a biomarker in axonal and myelin damage. Imaging Med. 2013;5(5):427-440. https://doi.org/10.2217/iim.13.49
Huang SY, Fan Q, Machado N, et al. Corpus callosum axon diameter relates to cognitive impairment in multiple sclerosis. Ann Clin Transl Neurol. 2019;6(5):882-892. https://doi.org/10.1002/acn3.760
Xie M, Tobin JE, Budde MD, et al. Rostrocaudal analysis of corpus callosum demyelination and axon damage across disease stages refines diffusion tensor imaging correlations with pathological features. J Neuropathol Exp Neurol. 2010;69(7):704-716. https://doi.org/10.1097/NEN.0b013e3181e3de90
Ryberg C, Rostrup E, Paulson OB, et al. Corpus callosum atrophy as a predictor of age-related cognitive and motor impairment: a 3-year follow-up of the LADIS study cohort. J Neurol Sci. 2011;307(1-2):100-105. https://doi.org/10.1016/j.jns.2011.05.002
Metzler-Baddeley C, Jones DK, Steventon J, et al. Cingulum microstructure predicts cognitive control in older age and mild cognitive impairment. J Neurosci. 2012;32(49):17612-17619. https://doi.org/10.1523/JNEUROSCI.3299-12.2012
Kim S, Choi SH, Lee YM, et al. Periventricular white matter hyperintensities and the risk of dementia: a CREDOS study. Int Psychogeriatr. 2015;27(12):2069-2077. https://doi.org/10.1017/S1041610215001076