The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
White matter lesions impair frontal lobe function regardless of their location
Open accessAbstract
OBJECTIVE: To analyze the effect of white matter lesions in different brain regions on regional cortical glucose metabolism, regional cortical atrophy, and cognitive function in a sample with a broad range of cerebrovascular disease and cognitive function. METHODS: Subjects (n = 78) were recruited for a study of subcortical ischemic vascular disease (SIVD) and Alzheimer disease (AD) contributions to dementia. A new method was developed to define volumes of interest from high-resolution three-dimensional T1-weighted MR images. Volumetric measures of MRI segmented white matter signal hyperintensities (WMH) in five different brain regions were related to regional PET glucose metabolism (rCMRglc) in cerebral cortex, MRI measures of regional cortical atrophy, and neuropsychological assessment of executive and memory function. RESULTS: WMH was significantly higher in the prefrontal region compared to the other brain regions. In all subjects, higher frontal and parietal WMH were associated with reduced frontal rCMRglc, whereas occipitotemporal WMH was only marginally associated with frontal rCMRglc. These associations were stronger and more widely distributed in nondemented subjects where reduced frontal rCMRglc was correlated with WMH for all regions measured. In contrast, there was no relationship between WMH in any brain region and rCMRglc in either parietal or occipitotemporal regions. WMHs in all brain regions were associated with low executive scores in nondemented subjects. CONCLUSIONS: The frontal lobes are most severely affected by SIVD. WMHs are more abundant in the frontal region. Regardless of where in the brain these WMHs are located, they are associated with frontal hypometabolism and executive dysfunction.
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“Previous studies investigating the impact of regional distribution of WMHs on executive function (EF) found that WMHs in all cortical regions (frontal areas, occipital, parietal and temporal) are associated with deficits in EF scores [15,16,17]”
From Amyloid-PET and White Matter Hyperintensities Have Independent Effects on Baseline Cognitive Function and Synergistic Effects on Longitudinal Executive Function (2023) · cites this paper as [17]
Experimental — accuracy not yet measuredIn the citing paper
“The demonstration of abnormalities on neuroimaging is critical for increased certainty in the diagnosis, and the lack of neuroimaging data can result in significant diagnostic inaccuracy by overlooking silent brain infarction and WMLs.37”
From Diagnostic Criteria for Vascular Cognitive Disorders: A VASCOG Statement (2014) · cites this paper as [37]
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Citations
Cites
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
Hirono, N., Mori, E., Ikejiri, Y., Imamura, T., Shimomura, T., Hashimoto, M., Yamashita, H., & Ikeda, M. (1997) · PubMed · Cited by 21,012
The Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882
A New Clinical Scale for the Staging of Dementia
Hughes, C. P., Berg, L., Danziger, W., Coben, L. A., & Martin, R. L. (1982) · British Journal of Psychiatry · doi:10.1192/bjp.140.6.566 · Cited by 7,056
Multimodality image registration by maximization of mutual information
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., & Suetens, P. (1997) · IEEE Transactions on Medical Imaging · doi:10.1109/42.563664 · Cited by 4,547
Frontal-subcortical circuits and human behavior
Cummings, J. L. (1993) · Archives of Neurology · doi:10.1001/archneur.1993.00540080076020 · Cited by 2,262
The Mini-Mental State Examination
Folstein, M. F. (1983) · Archives of General Psychiatry · doi:10.1001/archpsyc.1983.01790060110016 · Cited by 2,016
Brain Infarction and the Clinical Expression of Alzheimer Disease<subtitle>The Nun Study</subtitle>
Snowdon, D. A. (1997) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.1997.03540340047031 · Cited by 1,590
Frontal–subcortical neuronal circuits and clinical neuropsychiatry
Tekin, S., & Cummings, J. L. (2002) · Journal of Psychosomatic Research · doi:10.1016/s0022-3999(02)00428-2 · Cited by 1,240
Chui, H. C., Victoroff, J. I., Margolin, D., Jagust, W., Shankle, R., & Katzman, R. (1992) · Neurology · doi:10.1212/wnl.42.3.473 · Cited by 1,201
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Cited by
Sorted by citations
The Pathobiology of Vascular Dementia
Iadecola, C. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.008 · Cited by 1,857
“…structure and function broadly and are associated with reductions in frontal lobe glucose utilization (DeCarli et al., 1995; Haight et al., 2013; Tullberg et al., 2004), global reduction in cortical blood flow (Appelman et al., 2008; Chen et al., 2013a; ten Dam et al., 2007; Kobari et al.,…”
Peters, R. (2006) · Postgraduate Medical Journal · doi:10.1136/pgmj.2005.036665 · Cited by 894
Diagnostic Criteria for Vascular Cognitive Disorders: A VASCOG Statement
Sachdev, P., Kalaria, R., O’Brien, J., Skoog, I., Alladi, S., Black, S. E., Blacker, D., Blazer, D. G., Chen, C., Chui, H., et al. (2014) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0000000000000034 · Cited by 852
Self-citationThe overlap between vascular disease and Alzheimer’s disease - lessons from pathology
Attems, J., & Jellinger, K. A. (2014) · BMC Medicine · doi:10.1186/s12916-014-0206-2 · Cited by 739
“They impair frontal functions regardless of their location [175,176] and increase the risk of dementia, particularly in patients with lacunar infarcts [177,178], causing functional network disruption in cognitively-impaired individuals compared with age-matched healthy elderly controls [179,180].”
BackgroundYuan, P., & Raz, N. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.02.005 · Cited by 608
Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD
Yoshita, M., Fletcher, E., Harvey, D., Ortega, M., Martinez, O., Mungas, D. M., Reed, B. R., & DeCarli, C. S. (2006) · Neurology · doi:10.1212/01.wnl.0000249119.95747.1f · Cited by 434
Self-citationClinical, imaging, and pathological heterogeneity of the Alzheimer's disease syndrome
Lam, B., Masellis, M., Freedman, M., Stuss, D. T., & Black, S. E. (2013) · Alzheimer's Research & Therapy · doi:10.1186/alzrt155 · Cited by 386
Black, S., Gao, F., & Bilbao, J. (2009) · Stroke · doi:10.1161/strokeaha.108.537704 · Cited by 379
Au, R., Massaro, J. M., Wolf, P. A., Young, M. E., Beiser, A., Seshadri, S., D’Agostino, R. B., & DeCarli, C. (2006) · Archives of Neurology · doi:10.1001/archneur.63.2.246 · Cited by 381
Self-citationPathology and pathogenesis of vascular cognitive impairment—a critical update
Jellinger, K. A. (2013) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2013.00017 · Cited by 353
van Straaten, E. C. W., Fazekas, F., Rostrup, E., Scheltens, P., Schmidt, R., Pantoni, L., Inzitari, D., Waldemar, G., Erkinjuntti, T., Mäntylä, R., et al. (2006) · Stroke · doi:10.1161/01.str.0000202585.26325.74 · Cited by 314
Neuropathological basis of magnetic resonance images in aging and dementia
Jagust, W. J., Zheng, L., Harvey, D. J., Mack, W. J., Vinters, H. V., Weiner, M. W., Ellis, W. G., Zarow, C., Mungas, D., Reed, B. R., et al. (2008) · Annals of Neurology · doi:10.1002/ana.21296 · Cited by 302
Self-citationThe neurobiology of depression
Palazidou, E. (2012) · British Medical Bulletin · doi:10.1093/bmb/lds004 · Cited by 288
Measuring cognitive reserve based on the decomposition of episodic memory variance
Reed, B. R., Mungas, D., Farias, S. T., Harvey, D., Beckett, L., Widaman, K., Hinton, L., & DeCarli, C. (2010) · Brain · doi:10.1093/brain/awq154 · Cited by 271
Self-citationReed, B. R., Mungas, D. M., Kramer, J. H., Ellis, W., Vinters, H. V., Zarow, C., Jagust, W. J., & Chui, H. C. (2007) · Brain · doi:10.1093/brain/awl385 · Cited by 282
Self-citationBrain PET in Suspected Dementia: Patterns of Altered FDG Metabolism
Brown, R. K. J., Bohnen, N. I., Wong, K. K., Minoshima, S., & Frey, K. A. (2014) · RadioGraphics · doi:10.1148/rg.343135065 · Cited by 256
Acute effect of a high nitrate diet on brain perfusion in older adults
Presley, T. D., Morgan, A. R., Bechtold, E., Clodfelter, W., Dove, R. W., Jennings, J. M., Kraft, R. A., Bruce King, S., Laurienti, P. J., Jack Rejeski, W., et al. (2011) · Nitric Oxide · doi:10.1016/j.niox.2010.10.002 · Cited by 238
Vascular inflammation in cerebral small vessel disease
Rouhl, R. P. W., Damoiseaux, J. G. M. C., Lodder, J., Theunissen, R. O. M. F. I. H., Knottnerus, I. L. H., Staals, J., Henskens, L. H. G., Kroon, A. A., de Leeuw, P. W., Tervaert, J. W. C., et al. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2011.04.008 · Cited by 219
Sheline, Y. I., Price, J. L., Vaishnavi, S. N., Mintun, M. A., Barch, D. M., Epstein, A. A., Wilkins, C. H., Snyder, A. Z., Couture, L., Schechtman, K., et al. (2008) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2007.07010175 · Cited by 213
Bocti, C., Swartz, R. H., Gao, F.-Q., Sahlas, D. J., Behl, P., & Black, S. E. (2005) · Stroke · doi:10.1161/01.str.0000183615.07936.b6 · Cited by 182
Habes, M., Pomponio, R., Shou, H., Doshi, J., Mamourian, E., Erus, G., Nasrallah, I., Launer, L. J., Rashid, T., Bilgel, M., et al. (2021) · Alzheimer's & Dementia · doi:10.1002/alz.12178 · Cited by 173
Wright, C. B., Festa, J. R., Paik, M. C., Schmiedigen, A., Brown, T. R., Yoshita, M., DeCarli, C., Sacco, R., & Stern, Y. (2008) · Stroke · doi:10.1161/strokeaha.107.484147 · Cited by 171
Self-citationMorphologic diagnosis of “vascular dementia” — A critical update
Jellinger, K. A. (2008) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2008.03.006 · Cited by 150
Mixed dementia: A review of the evidence
Custodio, N., Montesinos, R., Lira, D., Herrera-Pérez, E., Bardales, Y., & Valeriano-Lorenzo, L. (2017) · Dementia & Neuropsychologia · doi:10.1590/1980-57642016dn11-040005 · Cited by 148
White matter lesions and brain atrophy: more than shared risk factors? A systematic review
Appelman, A. P. A., Exalto, L. G., van der Graaf, Y., Biessels, G. J., Mali, W. P. T. M., & Geerlings, M. I. (2009) · Cerebrovascular Diseases · doi:10.1159/000226774 · Cited by 130
White matter hyperintensities across the adult lifespan: Relation to age, Aβ load, and cognition
Garnier-Crussard, A., Bougacha, S., Wirth, M., André, C., Delarue, M., Landeau, B., Mézenge, F., Kuhn, E., Gonneaud, J., Chocat, A., et al. (2020) · Alzheimer's Research & Therapy · doi:10.1186/s13195-020-00669-4 · Cited by 130
Cerebrovascular disease, beta-amyloid, and cognition in aging
Marchant, N. L., Reed, B. R., DeCarli, C. S., Madison, C. M., Weiner, M. W., Chui, H. C., & Jagust, W. J. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2011.10.001 · Cited by 127
Self-citationKerrouche, N., Herholz, K., Mielke, R., Holthoff, V., & Baron, J.-C. (2006) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/sj.jcbfm.9600296 · Cited by 120
MTI of white matter hyperintensities
Fazekas, F., Ropele, S., Enzinger, C., Gorani, F., Seewann, A., Petrovic, K., & Schmidt, R. (2005) · Brain · doi:10.1093/brain/awh567 · Cited by 119
METACOHORTS Consortium, Dichgans, M., Wardlaw, J., Smith, E., Zietemann, V., Seshadri, S., Sachdev, P., Biessels, G. J., Fazekas, F., Benavente, O., et al. (2016) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.06.004 · Cited by 101
Self-citationCortical thinning related to periventricular and deep white matter hyperintensities
Seo, S. W., Lee, J.-M., Im, K., Park, J.-S., Kim, S.-H., Kim, S. T., Ahn, H.-J., Chin, J., Cheong, H.-K., Weiner, M. W., et al. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.12.003 · Cited by 95
Self-citationAribisala, B. S., Valdés Hernández, M. C., Royle, N. A., Morris, Z., Muñoz Maniega, S., Bastin, M. E., Deary, I. J., & Wardlaw, J. M. (2013) · European Radiology · doi:10.1007/s00330-012-2677-x · Cited by 91
Clinical effect of white matter network disruption related to amyloid and small vessel disease
Kim, H. J., Im, K., Kwon, H., Lee, J.-M., Kim, C., Kim, Y. J., Jung, N.-Y., Cho, H., Ye, B. S., Noh, Y., et al. (2015) · Neurology · doi:10.1212/wnl.0000000000001705 · Cited by 85
Self-citationRoseborough, A. D., Saad, L., Goodman, M., Cipriano, L. E., Hachinski, V. C., & Whitehead, S. N. (2023) · Alzheimer's & Dementia · doi:10.1002/alz.12642 · Cited by 80
Tract-specific white matter hyperintensities disrupt neural network function in Alzheimer’s disease
Taylor, A. N. W., Kambeitz-Ilankovic, L., Gesierich, B., Simon-Vermot, L., Franzmeier, N., Araque Caballero, M. Á., Müller, S., Hesheng, L., Ertl-Wagner, B., Bürger, K., et al. (2017) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.06.2358 · Cited by 73
Self-citationStudy, F. T. A., Brugulat-Serrat, A., Salvadó, G., Sudre, C. H., Grau-Rivera, O., Suárez-Calvet, M., Falcon, C., Sánchez-Benavides, G., Gramunt, N., Fauria, K., et al. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00151-2 · Cited by 64
Levy-Cooperman, N., Ramirez, J., Lobaugh, N. J., & Black, S. E. (2008) · Stroke · doi:10.1161/strokeaha.107.498196 · Cited by 52
Papma, J. M., den Heijer, T., de Koning, I., Mattace-Raso, F. U., van der Lugt, A., van der Lijn, F., van Swieten, J. C., Koudstaal, P. J., Smits, M., & Prins, N. D. (2013) · NeuroImage: Clinical · doi:10.1016/j.nicl.2012.11.005 · Cited by 48
Association of vascular brain injury, neurodegeneration, amyloid, and cognitive trajectory
Han, J. W., Maillard, P., Harvey, D., Fletcher, E., Martinez, O., Johnson, D. K., Olichney, J. M., Farias, S. T., Villeneuve, S., Jagust, W., et al. (2020) · Neurology · doi:10.1212/wnl.0000000000010531 · Cited by 49
Self-citationBiesbroek, J. M., Coenen, M., DeCarli, C., Fletcher, E. M., Maillard, P. M., Initiative, A. D. N., Barkhof, F., Barnes, J., Benke, T., Chen, C. P. L. H., et al. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.13765 · Cited by 38
Self-citationJoo, L., Shim, W. H., Suh, C. H., Lim, S. J., Heo, H., Kim, W. S., Hong, E., Lee, D., Sung, J., Lim, J.-S., et al. (2022) · PLOS ONE · doi:10.1371/journal.pone.0274562 · Cited by 35
Grigsby, J. (2016) · The Clinical Neuropsychologist · doi:10.1080/13854046.2016.1184652 · Cited by 34
White-matter lesions without lacunar infarcts in CADASIL
Benisty, S., Reyes, S., Godin, O., Hervé, D., Zieren, N., Jouvent, E., Zhu, Y., During, M., Dichgans, M., & Chabriat, H. (2012) · Journal of Alzheimer's Disease · doi:10.3233/jad-2012-111784 · Cited by 30
Wang, Z., Williams, V. J., Stephens, K. A., Kim, C., Bai, L., Zhang, M., & Salat, D. H. (2020) · Human Brain Mapping · doi:10.1002/hbm.24871 · Cited by 28
Scrascia, F., Curcio, G., Ursini, F., Trotta, L., Quintiliani, L., Migliore, S., Altamura, C., Pitocco, F., Altavilla, R., Melgari, J.-M., et al. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-130788 · Cited by 22
Vascular cognitive impairment: prodrome to VaD?
Mayda, A., & DeCarli, C. (2009) · Vascular Cognitive Impairment in Clinical Practice · doi:10.1017/cbo9780511575976.003 · Cited by 7
Self-citationAli, D. G., Abner, E. L., Bahrani, A. A., El Khouli, R., Gold, B. T., Jiang, Y., Wilcock, D. M., & Jicha, G. A. (2023) · Brain Sciences · doi:10.3390/brainsci13020218 · Cited by 6
Metadata
- Authors
- Tullberg, M., Fletcher, E., DeCarli, C., Mungas, D., Reed, B. R., Harvey, D. J., Weiner, M. W., Chui, H. C., & Jagust, W. J.
- Affiliations
- University of California, San Francisco (US)
- ORCID
- Venue
- Neurology
- Published
- 2004-07-27
- Volume
- 63
- Issue
- 2
- Pages
- 246-253
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- PMC
- PMC1893004
- OpenAlex
- W2077066095
- Cited by
- 530
- References
- 51
- Citations by year
- 2026: 13 · 2025: 11 · 2024: 12 · 2023: 17 · 2022: 16 · 2021: 19 · 2020: 27 · 2019: 27 · 2018: 17 · 2017: 21 · 2016: 24 · 2015: 30 · 2014: 32 · 2013: 36 · 2012: 25
- FWCI
- 16.99
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Neurology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (P30AG010129, AG 12435, AG-10129, P01AG012435, P50AG023501)
- National Institute of Neurological Disorders and Stroke (R01NS017950)
- Topics
- Health Sciences › Medicine › Clinical Neurology › Cerebrovascular and genetic disorders
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Neurology › Neurological Disease Mechanisms and Treatments
- Keywords
- white matter lesions, white matter hyperintensities, subcortical ischemic vascular disease, Alzheimer's disease, dementia, frontal lobe, regional cerebral glucose metabolism, frontal hypometabolism, cortical atrophy, executive function, memory, cerebrovascular disease, lesion localization
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Atrophy, Cognition Disorders, Female, Frontal Lobe, Glucose, Humans, Magnetic Resonance Imaging, Male, Memory Disorders, Myelin Sheath, Neuropsychological Tests, Dementia, Vascular, Positron-Emission Tomography
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