Cited by 316Cerebrovascular and genetic disordersAdvanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and Applications

The DOI matches its Crossref record; 49 of the 50 references it cites were found in a registry or an index.

The topography of white matter hyperintensities on brain MRI in healthy 60- to 64-year-old individuals

Wen, Wei, Sachdev, Perminder·2004·NeuroImage

DOI 10.1016/j.neuroimage.2003.12.027

Open this paper in CoChat — free account

Abstract

We report the topography of brain white matter hyperintensities (WMHs) on T2-weighted fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging in 477 healthy subjects aged 60-64 years selected randomly from the community. WMHs were delineated by using a computer algorithm. We found that all subjects had periventricular WMHs and 96.6% subjects also had deep WMHs. The mean volume of WMHs was 4.9 ml, comprising 0.83% of the white matter, of which 1.2 ml was severe in intensity. The deep WMHs were distributed throughout the cerebral hemispheres, with the occipital and frontal white matter bearing the greatest burden. The territory of the lenticulostriate arteries had the greatest WMHs. A white matter region of 4 mm adjacent to the cortex was not affected by hyperintensities. The mean (SD) number of discrete WMHs was 19.6 (7.1) per subject, of which 6.1 (4.4) were severe in intensity. Nearly half (48.6%) of the subjects had at least one large WMH (>12 mm diameter) and one eighth (12.5%) of the subjects had at least one large WMH that appeared to be severe in MRI. The overall load of WMHs was similar in men and women, but the latter had a higher proportion of their white matter so affected. This study provides the first detailed topographic analysis of WMHs in a large representative middle-aged sample, emphasizes their high prevalence in mid-adult life and raises issues about their etiology and significance.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1016/j.neuroimage.2003.12.027

Cites

49 of 49 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

“Mini-mental state”
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
Voxel-Based Morphometry—The Methods
Ashburner, J., & Friston, K. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0582 · Cited by 8,676
MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging
Fazekas, F., Chawluk, J. B., Alavi, A. A., Hurtig, H. I., & Zimmerman, R. A. (1987) · American Journal of Roentgenology · doi:10.2214/ajr.149.2.351 · Cited by 5,327
Pathologic correlates of incidental MRI white matter signal hyperintensities
Fazekas, F., Kleinert, R., Offenbacher, H., Schmidt, R., Kleinert, G., Payer, F., Radner, H., & Lechner, H. (1993) · Neurology · doi:10.1212/wnl.43.9.1683 · Cited by 1,619
Mapping brain asymmetry
Toga, A. W., & Thompson, P. M. (2003) · Nature reviews. Neuroscience · doi:10.1038/nrn1009 · Cited by 1,498
Clinical Correlates of White Matter Findings on Cranial Magnetic Resonance Imaging of 3301 Elderly People: The Cardiovascular Health Study
Longstreth, W. T., Manolio, T. A., Arnold, A., Burke, G. L., Bryan, N., Jungreis, C. A., Enright, P. L., O'Leary, D., & Fried, L. (1996) · Stroke · doi:10.1161/01.str.27.8.1274 · Cited by 1,464
Pathogenesis of Leukoaraiosis: A Review
Pantoni, L., & Garcia, J. H. (1997) · Stroke · doi:10.1161/01.str.28.3.652 · Cited by 1,225
Vascular Cognitive Impairment
O'Brien, J. T., Erkinjuntti, T., Reisberg, ‌., Román, G. C., Pantoni, L., Bowler, J., Ballard, C., DeCarli, C., Gorelick, P., Rockwood, K., et al. (2014) · International Journal of Stroke · doi:10.1111/ijs.12374_18 · Cited by 1,165
Multimodal image coregistration and partitioning--a unified framework.
Ashburner, J., & Friston, K. (1997) · NeuroImage · doi:10.1006/nimg.1997.0290 · Cited by 1,051
Cerebral white matter lesions, vascular risk factors, and cognitive function in a population‐based study
Breteler, M. M. B., Swieten, J. C. V., Bots, M. L., Grobbee, D. E., Claus, J. J., Hout, J. H. W. V. D., van Harskamp, F., Tanghe, H. L. J., de Jong, P. T. V. M., van Gijn, J., et al. (1994) · Neurology · doi:10.1212/wnl.44.7.1246 · Cited by 1,006

Flagged first, then by citations

Show all 50 references

1 of the 50 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

Moody, 1990, Does the tortuosity in cerebral arterioles impair down-regulation in hypertensive and elderly normotensive? A hypothesis and computer model, Clin. Neurosurg., 37, 372

Sorted by citations

Items 101–200 of 316

The relationship between carotid artery plaque stability and white matter ischemic injury
Berman, S. E., Wang, X., Mitchell, C., Kundu, B., Jackson, D. C., Wilbrand, S. M., Varghese, T., Hermann, B. P., Rowley, H. A., Johnson, S. C., et al. (2015) · NeuroImage Clinical · doi:10.1016/j.nicl.2015.08.011 · Cited by 50
Hormone replacement therapy, brain volumes and white matter in postmenopausal women aged 60–64 years
Low, L., Anstey, K. J., Maller, J. J., Kumar, R., Wen, W. X., Lux, O., Salonikas, C., Naidoo, D., & Sachdev, P. S. (2005) · Neuroreport · doi:10.1097/01.wnr.0000194385.10622.8e · Cited by 50
Self-citation
White matter hyperintensity shape and location feature analysis on brain MRI; proof of principle study in patients with diabetes
de Bresser, J., Kuijf, H. J., Zaanen, K., Viergever, M. A., Hendrikse, J., Biessels, G. J., Utrecht Vascular Cognitive Impairment Study Group, Algra, A., van den Berg, E., Bouvy, W. H., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-20084-y · Cited by 50
The Aging Brain and Executive Functions Revisited: Implications from Meta-analytic and Functional-Connectivity Evidence
Heckner, M. K., Cieslik, E. C., Eickhoff, S. B., Camilleri, J. A., Hoffstaedter, F., & Langner, R. (2020) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01616 · Cited by 53
Age differences in periventricular and deep white matter lesions
Nyquist, P., Bilgel, M., Gottesman, R. F., Yanek, L. R., Moy, T. F., Becker, L. C., Cuzzocreo, J. L., Prince, J. L., Wasserman, B. A., Yousem, D. M., et al. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.01.005 · Cited by 51
Amygdala in Stroke/Transient Ischemic Attack Patients and Its Relationship to Cognitive Impairment and Psychopathology: The Sydney Stroke Study
Sachdev, P. S., Chen, X., Joscelyne, A., Wen, W. X., & Brodaty, H. (2007) · American Journal of Geriatric Psychiatry · doi:10.1097/jgp.0b013e3180581fe6 · Cited by 49
Self-citation
Education, Atrophy, and Cognitive Change in an Epidemiological Sample in Early Old Age
Christensen, H., Batterham, P. J., Mackinnon, A. J., Anstey, K. J., Wen, W., & Sachdev, P. S. (2009) · The American Journal of Geriatric Psychiatry · doi:10.1097/jgp.0b013e3181961a84 · Cited by 48
Self-citation
Age-associated differences on structural brain MRI in nondemented individuals from 71 to 103 years
Yang, Z., Wen, W. X., Jiang, J., Crawford, J. D., Reppermund, S., Levitan, C., Slavin, M. J., Kochan, N. A., RICHMOND, R. L., Brodaty, H., et al. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.01.006 · Cited by 48
Self-citation
The Impact of Magnetic Resonance Imaging-Detected White Matter Hyperintensities on Longitudinal Changes in Regional Cerebral Blood Flow
Kraut, M. A., Beason‐Held, L. L., Elkins, W., & Resnick, S. M. (2007) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/sj.jcbfm.9600512 · Cited by 48
Morphologic, Distributional, Volumetric, and Intensity Characterization of Periventricular Hyperintensities
Hernández, M. C. V., Piper, R. J., Bastin, M. E., Royle, N. A., Maniega, S. M., Aribisala, B. S., Murray, C. L., Deary, I. J., & Wardlaw, J. M. (2013) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3612 · Cited by 47
The Genetics of White Matter Lesions
Assareh, A., Mather, K. A., Schofield, P. R., Kwok, J. B., & Sachdev, P. S. (2010) · CNS Neuroscience & Therapeutics · doi:10.1111/j.1755-5949.2010.00181.x · Cited by 46
Self-citation
Executive function mediates effects of white matter hyperintensities on episodic memory
Parks, C. M., Iosif, A., Farias, S. T., Reed, B., Mungas, D., & DeCarli, C. S. (2011) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2011.06.003 · Cited by 46
Optogenetic Stimulation of mPFC Alleviates White Matter Injury‐Related Cognitive Decline after Chronic Ischemia through Adaptive Myelination
Deng, S., Shu, S., Zhai, L., Xia, S., Cao, X., Li, H., Bao, X., Liu, P., & Xu, Y. (2022) · Advanced Science · doi:10.1002/advs.202202976 · Cited by 45
Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding
Sundaresan, V., Zamboni, G., Heron, C. J. L., Rothwell, P. M., Masud Husain, B., Battaglini, M., Stefano, N. D., Jenkinson, M., & Griffanti, L. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116056 · Cited by 46
Abnormalities of the Fornix in Mild Cognitive Impairment are Related to Episodic Memory Loss
Zhuang, L., Wen, W. X., Trollor, J. N., Kochan, N. A., Reppermund, S., Brodaty, H., & Sachdev, P. S. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-111766 · Cited by 46
Self-citation
Automated quantification of white matter lesion in magnetic resonance imaging of patients with acute infarction
Shi, L., Wang, D., Liu, S., Pu, Y., Wang, Y., Chu, C. W., Ahuja, A. T., & Wang, Y. (2012) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2012.12.014 · Cited by 44
Increased Visibility of Deep Medullary Veins in Leukoaraiosis: A 3-T MRI Study
Yan, S., Wan, J., Zhang, X., Tong, L., Zhao, S., Sun, J., Lin, Y., Shen, C., & Lou, M. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00144 · Cited by 44
Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study
Ribaldi, F., Altomare, D., Jovicich, J., Ferrari, C., Picco, A., Pizzini, F. B., Soricelli, A., Mega, A., Ferretti, A., Drevelegas, A., et al. (2020) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2020.11.008 · Cited by 44
Development and validation of morphological segmentation of age-related cerebral white matter hyperintensities
Beare, R. J., Srikanth, V. K., Chen, J., Phan, T. G., Stapleton, J., Lipshut, R., & Reutens, D. C. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.03.055 · Cited by 44
Automatic white matter lesion segmentation using an adaptive outlier detection method
Ong, K. H., Ramachandram, D., Mandava, R., & Shuaib, I. L. (2012) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2012.01.007 · Cited by 43
Individual variability of cerebral autoregulation, posterior cerebral circulation and white matter hyperintensity
Liu, J., Tseng, B. Y., Khan, M. A., Tarumi, T., Hill, C., Mirshams, N., Hodics, T. M., Hynan, L. S., & Zhang, R. (2016) · The Journal of Physiology · doi:10.1113/jp271068 · Cited by 46
Deep white matter hyperintensities, microstructural integrity and dual task walking in older people
Ghanavati, T., Smitt, M. S., Lord, S. R., Sachdev, P. S., Wen, W. X., Kochan, N. A., Brodaty, H., & Delbaere, K. (2018) · Brain Imaging and Behavior · doi:10.1007/s11682-017-9787-7 · Cited by 43
Self-citation
Mobility decline in the elderly relates to lesion accrual in the splenium of the corpus callosum
Moscufo, N., WOLFSON, L. I., Meier, D., Liguori, M., Hildenbrand, P. G., Wakefield, D. B., Schmidt, J. A., Pearlson, G. D., & Guttmann, C. R. G. (2011) · AGE · doi:10.1007/s11357-011-9242-4 · Cited by 42
White-matter degradation and dynamical compensation support age-related functional alterations in human brain
Petkoski, S., Ritter, P., & Jirsa, V. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac500 · Cited by 43
Hippocampal size and dementia in stroke patients: The Sydney stroke study
Sachdev, P. S., Chen, X., Joscelyne, A., Wen, W., Altendorf, A., & Brodaty, H. (2007) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2007.04.006 · Cited by 45
Self-citation
Spatial patterns of white matter hyperintensities: a systematic review
Botz, J., Lohner, V., & Schirmer, M. D. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1165324 · Cited by 40
Voxel-Based Assessment of Differences in Damage and Distribution of White Matter Lesions Between Patients With Primary Progressive and Relapsing-Remitting Multiple Sclerosis
Perri, C. D., Battaglini, M., Stromillo, M. L., Bartolozzi, M. L., Guidi, L., Federico, A., & Stefano, N. D. (2008) · Archives of Neurology · doi:10.1001/archneurol.2007.51 · Cited by 41
Application of variable threshold intensity to segmentation for white matter hyperintensities in fluid attenuated inversion recovery magnetic resonance images
Yoo, B. I., Lee, J. J., Han, J. W., Oh, S. Y. W., Lee, E. Y., MacFall, J. R., Payne, M. E., Kim, T. H., Kim, J. H., & Kim, K. W. (2014) · Neuroradiology · doi:10.1007/s00234-014-1322-6 · Cited by 40
Should We Distinguish Between Periventricular and Deep White Matter Hyperintensities?
Sachdev, P. S., & Wen, W. X. (2005) · Stroke · doi:10.1161/01.str.0000185694.52347.6e · Cited by 39
Self-citation
Late onset bipolar disorder associated with white matter hyperintensities: A pathophysiological hypothesis
Zanetti, M. V., Cordeiro, Q., & Busatto, G. F. (2006) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2006.10.004 · Cited by 38
Cerebral microbleeds are related to subjective cognitive failures: the RUN DMC study
van Norden, A. G. W., van Uden, I. W. M., de Laat, K. F., Gons, R. A. R., Kessels, R. P. C., van Dijk, E. J., & de Leeuw, F.-E. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.03.021 · Cited by 37
In vivo microstructural heterogeneity of white matter lesions in healthy elderly and Alzheimer's disease participants using tissue compositional analysis of diffusion MRI data
Mito, R., Dhollander, T., Xia, Y., Raffelt, D. A., Salvado, O., Churilov, L. P., Rowe, C. C., Brodtmann, A. G., Villemagne, V. L., & Connelly, A. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102479 · Cited by 37
The relationship of cerebral microbleeds to cognition and incident dementia in non-demented older individuals
Paradise, M., Seruga, A., Crawford, J. D., Chaganti, J. R., Thalamuthu, A., Kochan, N. A., Brodaty, H., Wen, W. X., & Sachdev, P. S. (2018) · Brain Imaging and Behavior · doi:10.1007/s11682-018-9883-3 · Cited by 38
Self-citation
Prevalence of White Matter Hyperintensity in Young Clinical Patients
Wang, M., Zhang, X.-X., Yu, M.-M., Li, W., & Li, Y. (2019) · American Journal of Roentgenology · doi:10.2214/ajr.18.20888 · Cited by 34
MR Imaging of Brain Volumes: Evaluation of a Fully Automatic Software
Ambarki, K., Wåhlin, A., Birgander, R., Eklund, A., & Malm, J. (2010) · American Journal of Neuroradiology · doi:10.3174/ajnr.a2275 · Cited by 34
Structural covariance of superficial white matter in mild Alzheimer's disease compared to normal aging
Carmeli, C., Fornari, E., Jalili, M., Meuli, R. A., & Knyazeva, M. G. (2014) · Brain and Behavior · doi:10.1002/brb3.252 · Cited by 32
Age and Alzheimer's pathology disrupt default mode network functioning via alterations in white matter microstructure but not hyperintensities
Brown, C., Jiang, Y., Smith, C. D., & Gold, B. T. (2018) · Cortex · doi:10.1016/j.cortex.2018.04.006 · Cited by 33
Vascular Cognitive Disorder
Paradise, M., & Sachdev, P. S. (2019) · Seminars in Neurology · doi:10.1055/s-0039-1678582 · Cited by 33
Self-citation
Three-tissue compositional analysis reveals in-vivo microstructural heterogeneity of white matter hyperintensities following stroke
Khan, W., Egorova, N., Khlif, M. S., Mito, R., Dhollander, T., & Brodtmann, A. G. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116869 · Cited by 33
Frontal and periventricular brain white matter lesions and cortical deafferentation of cholinergic and other neuromodulatory axonal projections.
Bohnen, N. I., Bogan, C., & Müller, M. L. T. M. (2009) · PubMed · Cited by 33
White Matter Hyperintensities are Positively Associated with Cortical Thickness in Alzheimer's Disease
Jacobs, H. I. L., Clerx, L., Gronenschild, E. H. B. M., Aalten, P., & Verhey, F. R. J. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-131232 · Cited by 35
Leukoaraiosis: Epidemiology, Imaging, Risk Factors, and Management of Age-Related Cerebral White Matter Hyperintensities
Huang, W.-Q., Lin, Q., & Tzeng, C. (2024) · Journal of Stroke · doi:10.5853/jos.2023.02719 · Cited by 35
The role of nutrition on cognition and brain health in ageing: a targeted approach
Monti, J. M., Moulton, C. J., & Cohen, N. J. (2015) · Nutrition Research Reviews · doi:10.1017/s0954422415000141 · Cited by 34
White Matter Hyperintensity Volume and Location: Associations With WM Microstructure, Brain Iron, and Cerebral Perfusion
Bauer, C. E., Zachariou, V., Seago, E. R., & Gold, B. T. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.617947 · Cited by 30
Signal abnormalities on 1.5 and 3 Tesla brain MRI in multiple sclerosis patients and healthy controls. A morphological and spatial quantitative comparison study
Perri, C. D., Dwyer, M. G., Wack, D. S., Cox, J. L., Hashmi, K., Saluste, E., Hussein, S. M., Schirda, C., Stosic, M., Durfee, J., et al. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.04.019 · Cited by 29
Combining multi-modality data for searching biomarkers in schizophrenia
Guo, S., Huang, C., Zhao, W. D., Yang, A. C., Lin, C., Nichols, T. E., & Tsai, S. (2018) · PLoS ONE · doi:10.1371/journal.pone.0191202 · Cited by 29
White matter hyperintensities in affected and unaffected late teenage and early adulthood offspring of bipolar parents: A two-center high-risk study
Gunde, E., Novák, T., Kopeček, M., Schmidt, M. H., Propper, L., Stopková, P., Höschl, C., Duffy, A. C., Alda, M., & Hájek, T. (2010) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2010.04.019 · Cited by 28
Affect of APOE on information processing speed in non-demented elderly population: a preliminary structural MRI study
Initiative, A. D. N., Luo, X., Jiaerken, Y., Yu, X., Huang, P., Qiu, T., Jia, Y., Sun, J., Zhou, J., & Zhang, M. (2016) · Brain Imaging and Behavior · doi:10.1007/s11682-016-9571-0 · Cited by 29
Genetic associations of leukoaraiosis indicate pathophysiological mechanisms in white matter lesions etiology
Lin, Q., Huang, W.-Q., & Tzeng, C. (2015) · Reviews in the Neurosciences · doi:10.1515/revneuro-2014-0082 · Cited by 28
The Relationship Between Plasma Aβ Levels, Cognitive Function and Brain Volumetrics: Sydney Memory and Ageing Study
Poljak, A., Crawford, J. D., Smythe, G. A., Brodaty, H., Slavin, M. J., Kochan, N. A., Trollor, J. N., Wen, W. X., Mather, K. A., Assareh, A. A., et al. (2015) · Current Alzheimer Research · doi:10.2174/1567205013666151218150202 · Cited by 28
Self-citation
Do white matter hyperintensities mediate the association between brain iron deposition and cognitive abilities in older people?
Hernández, M. D. C. V., Allerhand, M., Glatz, A., Clayson, L., Maniega, S. M., Gow, A. J., Royle, N. A., Bastin, M. E., Starr, J. M., Deary, I. J., et al. (2016) · European Journal of Neurology · doi:10.1111/ene.13006 · Cited by 28
Brain iron deposition in white matter hyperintensities: a 3-T MRI study
Yan, S., Sun, J., Chen, Y., Selim, M. H., & Lou, M. (2012) · AGE · doi:10.1007/s11357-012-9487-6 · Cited by 28
Automated identification of brain tumors from single MR images based on segmentation with refined patient-specific priors
Sanjuán, A., Price, C. J., Mancini, L., Josse, G., Grogan, A., Yamamoto, A. K., Geva, S., Leff, A. P., Yousry, T. A., & Seghier, M. L. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00241 · Cited by 27
Characterization of a normal control group: Are they healthy?
Aine, C. J., Sanfratello, L., Adair, J. C., Knoefel, J. E., Qualls, C., Lundy, S. L., Caprihan, A., Stone, D., & Stephen, J. M. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.09.025 · Cited by 26
Tractography at 3T MRI of Corpus Callosum Tracts Crossing White Matter Hyperintensities
Reginold, W., Itorralba, J., Luedke, A. C., Fernández-Ruíz, J., Reginold, J., Islam, O., & Garcia, A. A. (2016) · American Journal of Neuroradiology · doi:10.3174/ajnr.a4788 · Cited by 26
White matter hyperintensities and vascular risk factors in monozygotic twins
ten Kate, M., Sudre, C. H., den Braber, A., Konijnenberg, E., Nivard, M. G., Cardoso, M. J., Scheltens, P., Sebastien Ourselin, A., Boomsma, D. I., Barkhof, F., et al. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.02.002 · Cited by 25
Differential Regional Distribution of Juxtacortical White Matter Signal Abnormalities in Aging and Alzheimer’s Disease
Lindemer, E., Greve, D. N., Fischl, B. R., Augustinack, J. C., Salat, D. H., & Initiative, A. D. N. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-161057 · Cited by 24
Development and validation of a rating scale for perivascular spaces on 3T MRI
Paradise, M., Beaudoin, M. S., Dawes, L. C., Crawford, J. D., Wen, W. X., Brodaty, H., & Sachdev, P. S. (2019) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2019.116621 · Cited by 26
Self-citation
Regional differences in the link between water exchange rate across the blood–brain barrier and cognitive performance in normal aging
Zachariou, V., Pappas, C. A., Bauer, C. E., Shao, X., Liu, P., Lu, H., Wang, D. J. J., & Gold, B. T. (2023) · GeroScience · doi:10.1007/s11357-023-00930-2 · Cited by 21
Genetics of Microstructure of the Corpus Callosum in Older Adults
Kanchibhotla, S. C., Mather, K. A., Thalamuthu, A., Zhuang, L., Schofield, P. R., Kwok, J. B., Ames, D. J., Wright, M. J., Trollor, J. N., Wen, W. X., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0113181 · Cited by 21
Self-citation
Cognitive systems and the changing brain
Brigard, F. D. (2017) · Philosophical Explorations · doi:10.1080/13869795.2017.1312503 · Cited by 25
Brain White Matter Hyperintensity Lesion Characterization in T2 Fluid-Attenuated Inversion Recovery Magnetic Resonance Images: Shape, Texture, and Potential Growth
Gwo, C., Zhu, D. C., & Zhang, R. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00353 · Cited by 21
Sex-Specific Causes and Consequences of White Matter Damage in a Middle-Aged Cohort
Bonberg, N., Wulms, N., Nayyeri, M. D., Berger, K., & Minnerup, H. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.810296 · Cited by 23
Early Frontal Structural and Functional Changes in Mild White Matter Lesions Relevant to Cognitive Decline
Sun, X., Liang, Y., Wang, J., Chen, K., Chen, Y., Zhou, X., Jia, J., & Zhang, Z. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-131709 · Cited by 21
Enhancing Cognitive Fitness in Adults
Hartman-Stein, P. E., & Rue, A. L. (2011) · Springer eBooks · doi:10.1007/978-1-4419-0636-6 · Cited by 43
Abnormal intrinsic brain activity patterns in leukoaraiosis with and without cognitive impairment
Li, C., Yang, J., Yin, X., Liu, C., Zhang, L., Zhang, X., Gui, L., & Wang, J. (2015) · Behavioural Brain Research · doi:10.1016/j.bbr.2015.06.033 · Cited by 21
Specific locations within the white matter and cortex are involved in the cognitive impairments associated with periventricular white matter lesions (PWMLs)
Ding, X., Wu, J., Zhou, Z., & Zheng, J. (2015) · Behavioural Brain Research · doi:10.1016/j.bbr.2015.04.021 · Cited by 21
Impact of regional white matter lesions on cognitive function in subcortical vascular cognitive impairment
Ai, Q., Pu, Y., Sy, C. A., Liu, L., & Gao, P. (2014) · Neurological Research · doi:10.1179/1743132814y.0000000354 · Cited by 20
Renin-Angiotensin System Genetic Polymorphisms and Brain White Matter Lesions in Older Australians
Assareh, A. A., Mather, K. A., Crawford, J. D., Wen, W., Anstey, K. J., Easteal, S., Tan, X., Mack, H. A., Kwok, J. B., Schofield, P. R., et al. (2014) · American Journal of Hypertension · doi:10.1093/ajh/hpu035 · Cited by 20
Self-citation
Frontal lobe atrophy is associated with small vessel disease in ischemic stroke patients
Chen, Y., Chen, X., Xiao, W., Mok, V., Wong, K. S., & Tang, W. K. (2009) · Clinical Neurology and Neurosurgery · doi:10.1016/j.clineuro.2009.08.019 · Cited by 19
Association of small vessel ischemic white matter changes with BOLD fMRI imaging in the elderly
Patel, M. J., Boada, F. E., Price, J. C., Sheu, L. K., Tudorascu, D., Reynolds, C. F., & Aizenstein, H. J. (2012) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2012.09.006 · Cited by 19
Differentiating Mild Cognitive Impairment and Cognitive Changes of Normal Aging
Mosti, C. B., Rog, L. A., & Fink, J. W. (2019) · Clinical handbooks in neuropsychology · doi:10.1007/978-3-319-93497-6_28 · Cited by 18
Peak ependymal cell stretch overlaps with the onset locations of periventricular white matter lesions
Visser, V. L., Rusinek, H., & Weickenmeier, J. (2021) · Scientific Reports · doi:10.1038/s41598-021-00610-1 · Cited by 18
Bilateral Distance Partition of Periventricular and Deep White Matter Hyperintensities: Performance of the Method in the Aging Brain
Chen, J., Mikheev, A. V., Yu, H. Y., Gruen, M. D., Rusinek, H., & Ge, Y. (2020) · Academic Radiology · doi:10.1016/j.acra.2020.07.039 · Cited by 18
Association between periodontal disease and microstructural brain alterations in the Hamburg City Health Study
Mayer, C., Walther, C., Borof, K., Nägele, F. L., Petersen, M., Schell, M., Gerloff, C. P., Kühn, S., Heydecke, G., Beikler, T., et al. (2023) · Journal Of Clinical Periodontology · doi:10.1111/jcpe.13828 · Cited by 16
White matter hyperintensities, suicide risk and late-onset affective disorders: an overview of the current literature.
Pompili, M., Serafini, G., Innamorati, M., Serra, G., Forte, A. M., Lester, D., Ducci, G., Girardi, P., & Tatarelli, R. (2010) · PubMed · Cited by 16
Differential Impact of Acute Lesions Versus White Matter Hyperintensities on Stroke Recovery
Hawe, R. L., Findlater, S. E., Kenzie, J. M., Hill, M. D., Scott, S. H., & Dukelow, S. P. (2018) · Journal of the American Heart Association · doi:10.1161/jaha.118.009360 · Cited by 16
Automated measurement of local white matter lesion volume
van der Lijn, F., Verhaaren, B. F. J., Ikram, M. A., Klein, S., de Bruijne, M., Vrooman, H. A., Vernooij, M. W., Hammers, A., Rueckert, D., van der Lugt, A., et al. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.021 · Cited by 16
Microvessel stenosis, enlarged perivascular spaces, and fibrinogen deposition are associated with ischemic periventricular white matter hyperintensities
Roseborough, A. D., Rasheed, B., Jung, Y., Nishimura, K., Pinsky, W., Langdon, K. D., Hammond, R. R., Pasternak, S., KHAN, A. R., & Whitehead, S. N. (2021) · Brain Pathology · doi:10.1111/bpa.13017 · Cited by 15
Reliability of two techniques for assessing cerebral iron deposits with structural magnetic resonance imaging
Hernández, M. C. V., Jeong, T. H., Murray, C. L., Bastin, M. E., Chappell, F. M., Deary, I. J., & Wardlaw, J. M. (2010) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.22361 · Cited by 16
The challenge of cerebral magnetic resonance imaging in neonates: A new method using mathematical morphology for the segmentation of structures including diffuse excessive high signal intensities.
Xu, Y., Morel, B., Dahdouh, S., Puybareau, É., Virzì, A., Urien, H., Géraud, T., Adamsbaum, C., & Isabelle Bloch, A. (2018) · Medical Image Analysis · doi:10.1016/j.media.2018.05.003 · Cited by 15
Relevance of brain lesion location for cognition in vascular mild cognitive impairment
Giorgio, A., Donato, I. D., Leucio, A. D., Zhang, J., Salvadori, E., Poggesi, A., Diciotti, S., Cosottini, M., Ciulli, S., Inzitari, D., et al. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101789 · Cited by 18
White Matter Lesions in Patients With Localization-Related Epilepsy
Jansen, J. F. A., Vlooswijk, M. C. G., Majoie, M., de Krom, M. C. T. F. M., Aldenkamp, A. P., Hofman, P. A. M., & Backes, W. H. (2008) · Investigative Radiology · doi:10.1097/rli.0b013e31817e90d2 · Cited by 15
Prediction of cognitive decline after stroke using proton magnetic resonance spectroscopy
Ross, A. J., Sachdev, P. S., Wen, W. X., Brodaty, H., Joscelyne, A., & Lorentz, L. (2006) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2006.08.014 · Cited by 15
Self-citation
Vascular cognitive impairment and dementia: Prevention, treatments, mechanisms and management options for the future
Lennon, M. J., & Sachdev, P. S. (2026) · Neuropsychopharmacology · doi:10.1038/s41386-026-02331-3 · Cited by 15
Self-citation
Imaging of Normal Brain Aging
Ota, Y., & Shah, G. V. (2022) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2022.04.010 · Cited by 17
Magnetic Resonance Image Analysis for Brain CAD Systems with Machine Learning
Arimura, H., Tokunaga, C., Yamashita, Y., & Kuwazuru, J. (2012) · Advances in bioinformatics and biomedical engineering book series · doi:10.4018/978-1-4666-0059-1.ch013 · Cited by 14
White Matter Lesions and Vascular Cognitive Impairment
Nichtweiß, M., Weidauer, S., Treusch, N., & Hattingen, E. (2012) · Clinical Neuroradiology · doi:10.1007/s00062-012-0134-5 · Cited by 14
Current Status and Future Perspectives of Magnetic Resonance High-Field Imaging: A Summary
Prabhakaran, V., Nair, V. A., Austin, B. P., La, C., Gallagher, T. A., Wu, Y., McLaren, D. G., Xu, G., Turski, P. A., & Rowley, H. A. (2012) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2012.02.012 · Cited by 14
Structural MRI Biomarkers of Mild Cognitive Impairment from Young Elders to Centenarians
Yang, Z., Wen, W. X., Jiang, J., Crawford, J. D., Reppermund, S., Levitan, C., Slavin, M. J., Kochan, N. A., RICHMOND, R. L., Brodaty, H., et al. (2016) · Current Alzheimer Research · doi:10.2174/1567205013666151218150534 · Cited by 14
Self-citation
Brain MRI, Apoliprotein E Genotype, and Plasma Homocysteine in American Indian Alzheimer Disease Patients and Indian Controls
Weiner, M., de la Plata, C., Fields, B. J., Womack, K. B., Rosenberg, R. N., Gong, Y.-H., Qu, B., Diaz-Arrastia, R. R., & Hynan, L. S. (2009) · Current Alzheimer Research · doi:10.2174/156720509787313952 · Cited by 14
Incidental findings on cerebral MRI in twins: the Older Australian Twins Study
Koncz, R., Mohan, A., Dawes, L. C., Thalamuthu, A., Wright, M. J., Ames, D. J., Lee, T., Trollor, J. N., Wen, W. X., & Sachdev, P. S. (2017) · Brain Imaging and Behavior · doi:10.1007/s11682-017-9747-2 · Cited by 13
Self-citation
Current and Emerging Therapeutic Approaches for Vascular Cognitive Impairment and Dementia
Goodall, L., Lennon, M. J., Sachdev, P. S., Gorelick, P. B., Kovacic, J. C., & Samaras, K. (2026) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2025.09.1502 · Cited by 14
Self-citation
White matter hyperintensity spatial patterns: Risk factors and clinical correlates
Beyer, F., Tsuchida, A., Soumaré, A., Rajula, H. S. R., Mishra, A., Crivello, F., Proust‐Lima, C., Loeffler, M., Tzourio, C., Amouyel, P., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70053 · Cited by 16
Reliability of two techniques for assessing cerebral iron deposits from structural MRI
Hernández, M. C. V., Jeong, T. H., Murray, C. L., Bastin, M. E., Chappell, F. M., Deary, I. J., & Wardlaw, J. M. (2011) · ERA · doi:10.1002/jmri.22361/abstract · Cited by 12
White matter hyperintensities and impaired choice stepping reaction time in older people
Zheng, J. J. J., Delbaere, K., Close, J., Sachdev, P. S., Wen, W. X., & Lord, S. R. (2011) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.12.009 · Cited by 12
Self-citation
The MRI central vein marker; differentiating PPMS from RRMS and ischemic SVD
Samaraweera, A. P. R., Falah, Y., Pitiot, A., Dineen, R. A., Morgan, P. S., & Evangelou, N. (2018) · Neurology Neuroimmunology & Neuroinflammation · doi:10.1212/nxi.0000000000000496 · Cited by 12
The cerebellar white matter lesions in dentatorubral-pallidoluysian atrophy
Sugiyama, A., Sato, N., Kimura, Y., Fujii, H., Shigemoto, Y., Suzuki, F., Tanei, Z., Saito, Y., Sasaki, M., Takahashi, Y. K., et al. (2020) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2020.117040 · Cited by 12
Interaction of white matter hyperintensities (WMHs) and apolipoprotein E (APOE) genotypes on cognition in patients with amnestic mild cognitive impairment (aMCI)
Yoon, B., Shim, Y. S., Cheong, H., Kim, Y.-D., Lee, K. O., Hong, Y. J., Oh, Y., Na, H. R., Kim, B., Choi, S. H., et al. (2013) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2013.04.008 · Cited by 12
Disentangling the pathologies linking white matter hyperintensity and geriatric depressive symptoms in subjects with different degrees of vascular impairment
Zhang, R., Yu, W., Wu, X. H., Jiaerken, Y., Wang, S., Hong, H., Li, K., Zeng, Q., Luo, X., Yu, X., et al. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.12.171 · Cited by 12

Authors: Wen, W., & Sachdev, P.
Affiliations: UNSW Sydney (AU)
Corresponding author: Sachdev, Perminder
ORCID: Wen, Wei
Sachdev, Perminder
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2004-05
Volume: 22
Issue: 1
Pages: 144-154
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2003.12.027
OpenAlex: W2070268750
Cited by: 315
References: 50
Citations by year: 2026: 6 · 2025: 15 · 2024: 8 · 2023: 13 · 2022: 13 · 2021: 18 · 2020: 8 · 2019: 12 · 2018: 14 · 2017: 13 · 2016: 14 · 2015: 13 · 2014: 19 · 2013: 15 · 2012: 19
FWCI: 9.11
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
Funders: University of New South Wales
National Health and Medical Research Council
Topics: Health Sciences › Medicine › Clinical Neurology › Cerebrovascular and genetic disorders
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Keywords: white matter hyperintensities, periventricular white matter, deep white matter hyperintensities, FLAIR MRI, lenticulostriate arteries, white matter volume, middle-aged adults, sex differences, prevalence, white matter disease
MeSH terms: Aging, Australia, Brain, Brain Mapping, Cerebral Arteries, Education, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Neuropsychological Tests, Psychiatric Status Rating Scales, Reference Values, Sex Characteristics, Reproducibility of Results

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

The topography of white matter hyperintensities on brain MRI in healthy 60- to 64-year-old individuals

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks