Association of Neuroimaging Markers on Clinical CT Scans With Domain-Specific Cognitive Impairment in the Early and Later Poststroke Stages

Overview

Journal Neurology

Specialty Neurology

Date 2023 Sep 1

PMID 37657938

Authors

Georgina Hobden

Margaret J Moore

Emma Colbourne

Sarah T Pendlebury

Nele Demeyere

Affiliations

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Abstract

Background And Objectives: Poststroke cognitive impairment (PSCI) is associated with neuroimaging markers, including cortical atrophy and white matter lesions (WMLs), on clinically acquired CT neuroimaging. The objective was to investigate the association between cortical atrophy/WMLs and PSCI in specific cognitive domains in the acute/subacute and chronic stages after stroke, to provide clarity on the relationship between these neuroimaging markers and the temporal evolution of PSCI.

Methods: We visually assessed cortical atrophy using the Global Cortical Atrophy (GCA) scale and WMLs using the Fazekas scale. Oxford Cognitive Screen or Birmingham Cognitive Screen assessed PSCI at 2 time points (acute/subacute and chronic) in 6 domains (language, memory, number processing, executive function, attention, and praxis). We binarized domain-specific performance as impaired/unimpaired using normative cutoffs. Multivariable linear and logistic regression analyses evaluated associations between GCA/Fazekas scores with acute/subacute and chronic global and domain-specific PSCI, and ANCOVAs examined whether these scores were significantly different in patients with recovered vs persistent PSCI. Age, sex, education, NIHSS, lesion volume, and recurrent stroke were covariates in these analyses.

Results: Among 411 stroke patients (Mdn/IQR age = 76.16/66.84-83.47; 193 female; 346 ischemic stroke; 107 recurrent stroke), GCA and Fazekas scores were not associated with global cognitive impairment in the acute/subacute stage after stroke, but GCA score was associated with chronic global PSCI ( = 0.01, < 0.001, 95% CI 0.00-0.01). In domain-specific analyses, GCA score was associated with chronic impairment in the memory ( = 0.06, < 0.001, 95% CI 0.03-0.10) and attention ( = 0.05, = 0.003, 95% CI 0.02-0.09) domains, and in patients with persistent PSCI, these domains showed significantly higher GCA scores than patients who had recovered (memory: (1, 157) = 6.63, = 0.01, = 0.04; attention: (1, 268) = 10.66, = 0.001, 0.04).

Discussion: This study highlights the potential effect of cortical atrophy on the cognitive recovery process after stroke and demonstrates the prognostic utility of CT neuroimaging for poststroke cognitive outcomes. Clinical neuroimaging could help identify patients at long-term risk of PSCI during acute hospitalization.

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References

Mijajlovic M, Pavlovic A, Brainin M, Heiss W, Quinn T, Ihle-Hansen H . Post-stroke dementia - a comprehensive review. BMC Med. 2017; 15(1):11. PMC: 5241961. DOI: 10.1186/s12916-017-0779-7. View

Rudilosso S, San Roman L, Blasco J, Hernandez-Perez M, Urra X, Chamorro A . Evaluation of white matter hypodensities on computed tomography in stroke patients using the Fazekas score. Clin Imaging. 2017; 46:24-27. DOI: 10.1016/j.clinimag.2017.06.011. View

Saini M, Tan C, Hilal S, Dong Y, Ting E, Ikram M . Computer tomography for prediction of cognitive outcomes after ischemic cerebrovascular events. J Stroke Cerebrovasc Dis. 2014; 23(7):1921-7. DOI: 10.1016/j.jstrokecerebrovasdis.2014.02.007. View

Graham J . Missing data analysis: making it work in the real world. Annu Rev Psychol. 2008; 60:549-76. DOI: 10.1146/annurev.psych.58.110405.085530. View

Brickman A, Honig L, Scarmeas N, Tatarina O, Sanders L, Albert M . Measuring cerebral atrophy and white matter hyperintensity burden to predict the rate of cognitive decline in Alzheimer disease. Arch Neurol. 2008; 65(9):1202-8. PMC: 2629007. DOI: 10.1001/archneur.65.9.1202. View

Ball E, Sutherland R, Squires C, Mead G, Religa D, Lundstrom E . Predicting post-stroke cognitive impairment using acute CT neuroimaging: A systematic review and meta-analysis. Int J Stroke. 2021; 17(6):618-627. PMC: 9260488. DOI: 10.1177/17474930211045836. View

Roccaforte W, BURKE W, Bayer B, Wengel S . Validation of a telephone version of the mini-mental state examination. J Am Geriatr Soc. 1992; 40(7):697-702. DOI: 10.1111/j.1532-5415.1992.tb01962.x. View

Sexton E, McLoughlin A, Williams D, Merriman N, Donnelly N, Rohde D . Systematic review and meta-analysis of the prevalence of cognitive impairment no dementia in the first year post-stroke. Eur Stroke J. 2019; 4(2):160-171. PMC: 6591758. DOI: 10.1177/2396987318825484. View

Iosa M, Demeyere N, Abbruzzese L, Zoccolotti P, Mancuso M . Principal Component Analysis of Oxford Cognitive Screen in Patients With Stroke. Front Neurol. 2022; 13:779679. PMC: 9197217. DOI: 10.3389/fneur.2022.779679. View

10.

Moon Y, Kim S, Kim H, Won M, Kim D . Correlates of quality of life after stroke. J Neurol Sci. 2004; 224(1-2):37-41. DOI: 10.1016/j.jns.2004.05.018. View

11.

Hobden G, Colbourne E, Pendlebury S, Demeyere N . Reliability of the global cortical atrophy visual rating scale applied to computed tomography versus magnetic resonance imaging scans in acute stroke. Neurol Sci. 2023; 45(4):1549-1556. PMC: 10942897. DOI: 10.1007/s10072-023-07113-z. View

12.

Paul S, Sturm J, Dewey H, Donnan G, Macdonell R, Thrift A . Long-term outcome in the North East Melbourne Stroke Incidence Study: predictors of quality of life at 5 years after stroke. Stroke. 2005; 36(10):2082-6. DOI: 10.1161/01.STR.0000183621.32045.31. View

13.

Jokinen H, Lipsanen J, Schmidt R, Fazekas F, Gouw A, van der Flier W . Brain atrophy accelerates cognitive decline in cerebral small vessel disease: the LADIS study. Neurology. 2012; 78(22):1785-92. DOI: 10.1212/WNL.0b013e3182583070. View

14.

Brazzelli M, Sandercock P, Chappell F, Celani M, Righetti E, Arestis N . Magnetic resonance imaging versus computed tomography for detection of acute vascular lesions in patients presenting with stroke symptoms. Cochrane Database Syst Rev. 2009; (4):CD007424. DOI: 10.1002/14651858.CD007424.pub2. View

15.

Jacquin A, Binquet C, Rouaud O, Graule-Petot A, Daubail B, Osseby G . Post-stroke cognitive impairment: high prevalence and determining factors in a cohort of mild stroke. J Alzheimers Dis. 2014; 40(4):1029-38. DOI: 10.3233/JAD-131580. View

16.

Demeyere N, Riddoch M, Slavkova E, Jones K, Reckless I, Mathieson P . Domain-specific versus generalized cognitive screening in acute stroke. J Neurol. 2015; 263(2):306-315. PMC: 4751179. DOI: 10.1007/s00415-015-7964-4. View

17.

Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V . Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012; 380(9859):2095-128. PMC: 10790329. DOI: 10.1016/S0140-6736(12)61728-0. View

18.

Godin O, Tzourio C, Rouaud O, Zhu Y, Maillard P, Pasquier F . Joint effect of white matter lesions and hippocampal volumes on severity of cognitive decline: the 3C-Dijon MRI study. J Alzheimers Dis. 2010; 20(2):453-63. DOI: 10.3233/JAD-2010-1389. View

19.

Fazekas F, Chawluk J, Alavi A, Hurtig H, Zimmerman R . MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging. AJR Am J Roentgenol. 1987; 149(2):351-6. DOI: 10.2214/ajr.149.2.351. View

20.

Hobden G, Moore M, Mair G, Pendlebury S, Demeyere N . Poststroke Executive Function in Relation to White Matter Damage on Clinically Acquired CT Brain Imaging. Cogn Behav Neurol. 2023; 37(1):23-31. DOI: 10.1097/WNN.0000000000000355. View