The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Total MRI load of cerebral small vessel disease and cognitive ability in older people
Open accessAbstract
Cerebral small vessel disease (SVD) may cause cognitive dysfunction. We tested the association between the combined presence of magnetic resonance imaging (MRI) features of SVD and cognitive ability in older age. Cognitive testing and brain MRI were performed in 680 older participants. MRI presence of lacunes, white matter hyperintensities, microbleeds, and perivascular spaces were summed in a score of 0-4 representing all SVD features combined. We also applied latent variable modeling to test whether the 4 MRI features form a unitary SVD construct. The SVD score showed significant associations with general cognitive ability. Latent variable modeling indicated that the 4 MRI markers formed a unitary construct, which showed consistent associations with cognitive ability compared with the SVD score. Total MRI load of SVD is associated with lower general cognitive ability in older age. The total SVD score performed consistently with the more complex latent variable model, suggesting validity and potential utility in future research for determining total SVD load.
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Cites
MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging
Fazekas, F., Chawluk, J., Alavi, A., Hurtig, H., & Zimmerman, R. (1987) · American Journal of Roentgenology · doi:10.2214/ajr.149.2.351 · Cited by 5,334
Gorelick, P. B., Scuteri, A., Black, S. E., DeCarli, C., Greenberg, S. M., Iadecola, C., Launer, L. J., Laurent, S., Lopez, O. L., Nyenhuis, D., et al. (2011) · Stroke · doi:10.1161/str.0b013e3182299496 · Cited by 3,811
Pantoni, L. (2010) · The Lancet Neurology · doi:10.1016/s1474-4422(10)70104-6 · Cited by 3,405
Debette, S., & Markus, H. S. (2010) · BMJ · doi:10.1136/bmj.c3666 · Cited by 2,328
Silent Brain Infarcts and the Risk of Dementia and Cognitive Decline
Vermeer, S. E., Prins, N. D., den Heijer, T., Hofman, A., Koudstaal, P. J., & Breteler, M. M. B. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa022066 · Cited by 2,313
Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging
Wardlaw, J. M., Smith, C., & Dichgans, M. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70060-7 · Cited by 1,657
Self-citationSilent brain infarcts: a systematic review
Vermeer, S. E., Longstreth, W. T., & Koudstaal, P. J. (2007) · The Lancet Neurology · doi:10.1016/s1474-4422(07)70170-9 · Cited by 1,221
Stroke subtype, vascular risk factors, and total MRI brain small-vessel disease burden
Staals, J., Makin, S. D. J., Doubal, F. N., Dennis, M. S., & Wardlaw, J. M. (2014) · Neurology · doi:10.1212/wnl.0000000000000837 · Cited by 1,039
Self-citationEnlarged perivascular spaces on MRI are a feature of cerebral small vessel disease
Doubal, F. N., MacLullich, A. M. J., Ferguson, K. J., Dennis, M. S., & Wardlaw, J. M. (2010) · Stroke · doi:10.1161/strokeaha.109.564914 · Cited by 904
Self-citationDeary, I. J., Whiteman, M. C., Starr, J. M., Whalley, L. J., & Fox, H. C. (2004) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.86.1.130 · Cited by 809 · cited 3×
“Age 11 IQ was computed from the scores on the validated Moray House Test (Deary et al., 2004a, 2007) that was taken in 1947.”
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Neuroimaging standards for research into small vessel disease—advances since 2013
Duering, M., Biessels, G. J., Brodtmann, A., Chen, C., Cordonnier, C., de Leeuw, F.-E., Debette, S., Frayne, R., Jouvent, E., Rost, N. S., et al. (2023) · The Lancet Neurology · doi:10.1016/s1474-4422(23)00131-x · Cited by 1,144
Self-citationPerivascular spaces in the brain: anatomy, physiology and pathology
Wardlaw, J. M., Benveniste, H., Nedergaard, M., Zlokovic, B. V., Mestre, H., Lee, H., Doubal, F. N., Brown, R., Ramirez, J., MacIntosh, B. J., et al. (2020) · Nature Reviews Neurology · doi:10.1038/s41582-020-0312-z · Cited by 870
Self-citationInflammation and cerebral small vessel disease: A systematic review
Low, A., Mak, E., Rowe, J. B., Markus, H. S., & O’Brien, J. T. (2019) · Ageing Research Reviews · doi:10.1016/j.arr.2019.100916 · Cited by 444
Epidemiology of Vascular Dementia: Nosology in a Time of Epiomics
Wolters, F. J., & Ikram, M. A. (2019) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/atvbaha.119.311908 · Cited by 403
Understanding the role of the perivascular space in cerebral small vessel disease
Brown, R., Benveniste, H., Black, S. E., Charpak, S., Dichgans, M., Joutel, A., Nedergaard, M., Smith, K. J., Zlokovic, B. V., & Wardlaw, J. M. (2018) · Cardiovascular Research · doi:10.1093/cvr/cvy113 · Cited by 336
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Metadata
- Authors
- Staals, J., Booth, T., Morris, Z., Bastin, M. E., Gow, A. J., Corley, J., Redmond, P., Starr, J. M., Deary, I. J., & Wardlaw, J. M.
- Venue
- Neurobiology of Aging
- Publisher
- Elsevier BV
- Published
- 2015-10
- Volume
- 36
- Issue
- 10
- Pages
- 2806-2811
- ISSN
- 0197-4580 (ISSN-L)
- OpenAlex
- W2118636048
- Cited by
- 262
- References
- 40
- FWCI
- 12.15
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Staals, J., Booth, T., Morris, Z., Bastin, M. E., Gow, A. J., Corley, J., Redmond, P., Starr, J. M., Deary, I. J., & Wardlaw, J. M. (2015). Total MRI load of cerebral small vessel disease and cognitive ability in older people. Neurobiology of Aging. https://doi.org/10.1016/j.neurobiolaging.2015.06.024
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