Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-22T23:17:31.684Z Has data issue: false hasContentIssue false

White Matter Predictors of Cognitive Functioning in Older Adults

Published online by Cambridge University Press:  06 March 2012

Irene B. Meier
Affiliation:
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
Jennifer J. Manly
Affiliation:
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, New York Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
Frank A. Provenzano
Affiliation:
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
Karmen S. Louie
Affiliation:
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
Ben T. Wasserman
Affiliation:
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
Erica Y. Griffith
Affiliation:
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
Josina T. Hector
Affiliation:
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
Elizabeth Allocco
Affiliation:
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
Adam M. Brickman*
Affiliation:
Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, New York Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
*
Correspondence and reprint requests to: Adam M. Brickman, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, P&S Box 16, New York, NY 10032. E-mail: [email protected]

Abstract

Few studies have applied multiple imaging modalities to examine cognitive correlates of white matter. We examined the utility of T2-weighted magnetic resonance imaging (MRI) -derived white matter hyperintensities (WMH) and diffusion tensor imaging-derived fractional anisotropy (FA) to predict cognitive functioning among older adults. Quantitative MRI and neuropsychological evaluations were performed in 112 older participants from an ongoing study of the genetics of Alzheimer's disease (AD) in African Americans. Regional WMH volumes and FA were measured in multiple regions of interest. We examined the association of regional WMH and an FA summary score with cognitive test performance. Differences in WMH and FA were compared across diagnostic groups (i.e., normal controls, mild cognitive impairment, and probable AD). Increased WMH volume in frontal lobes was associated with poorer delayed memory performance. FA did not emerge as a significant predictor of cognition. White matter hyperintensity volume in the frontal and parietal lobes was increased in MCI participants and more so in AD patients relative to controls. These results highlight the importance of regionally distributed small vessel cerebrovascular disease in memory performance and AD among African American older adults. White matter microstructural changes, quantified with diffusion tensor imaging, appear to play a lesser role in our sample. (JINS, 2012, 18, 414–427)

Type
Research Articles
Copyright
Copyright © The International Neuropsychological Society 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Admiraal-Behloul, F., Olofesen, H., Van den Heuvel, D. M., Schmitz, N., Reiber, J. H., Van Buchem, M. A. (2004). Fully automated lobe delineation for regional white matter lesion load quantification in a large scale study. Proceedings of the International Society for Magnetic Resonance in Medicine. 138.Google Scholar
American Psychiatric, A. (1994). Diagnostic and statistical manual of mental disorders, fourth edition. Washington, DC: American Psychiatric Press.Google Scholar
Barber, R., Gholkar, A., Scheltens, P., Ballard, C., McKeith, I.G., O'Brien, J.T. (1999). Medial temporal lobe atrophy on MRI in dementia with Lewy bodies. Neurology, 52(6), 11531158.CrossRefGoogle ScholarPubMed
Basser, P.J., Pajevic, S., Pierpaoli, C., Duda, J., Aldroubi, A. (2000). In vivo fiber tractography using DT-MRI data. Magnetic Resonance in Medicine, 44(4), 625632.Google Scholar
Benton, A.L., Hamsher, K.D. (1976). Multilingual aphasia examination. Iowa City, IA: University of Iowa.Google Scholar
Bozzali, M., Falini, A., Franceschi, M., Cercignani, M., Zuffi, M., Scotti, G., Filippi, M. (2002). White matter damage in Alzheimer's disease assessed in vivo using diffusion tensor magnetic resonance imaging. Journal of Neurology, Neurosurgery, & Psychiatry, 72(6), 742746.CrossRefGoogle ScholarPubMed
Brickman, A.M., Honig, L.S., Scarmeas, N., Tatarina, O., Sanders, L., Albert, M.S., Stern, Y. (2008). Measuring cerebral atrophy and white matter hyperintensity burden to predict the rate of cognitive decline in Alzheimer disease. Archives of Neurology, 65(9), 12021208.CrossRefGoogle ScholarPubMed
Brickman, A.M., Muraskin, J., Zimmerman, M.E. (2009). Structural neuroimaging in Alzheimer's disease: Do white matter hyperintensities matter? Dialogues in Clinical Neuroscience, 11(2), 181190.CrossRefGoogle ScholarPubMed
Brickman, A.M., Reitz, C., Luchsinger, J.A., Manly, J.J., Schupf, N., Muraskin, J., Mayeux, R. (2010). Long-term blood pressure fluctuation and cerebrovascular disease in an elderly cohort. Archives of Neurology, 67(5), 564569.Google Scholar
Brickman, A.M., Schupf, N., Manly, J.J., Luchsinger, J.A., Andrews, H., Tang, M.X., Brown, T.R. (2008). Brain morphology in older African Americans, Caribbean Hispanics, and whites from northern Manhattan. Archives of Neurology, 65(8), 10531061.CrossRefGoogle ScholarPubMed
Brickman, A.M., Sneed, J.R., Provenzano, F.A., Garcon, E., Johnert, L., Muraskin, J., Roose, S.P. (2011). Quantitative approaches for assessment of white matter hyperintensities in elderly populations. Psychiatry Research, 193(2), 101106. doi:S0925-4927(11)00116-8 [pii] 10.1016/j.pscychresns.2011.03.007CrossRefGoogle ScholarPubMed
Brun, A., Englund, E. (1981). Regional pattern of degeneration in Alzheimer's disease: Neuronal loss and histopathological grading. Histopathology, 5(5), 549564.CrossRefGoogle ScholarPubMed
Burns, J.M., Church, J.A., Johnson, D.K., Xiong, C., Marcus, D., Fotenos, A.F., Buckner, R.L. (2005). White matter lesions are prevalent but differentially related with cognition in aging and early Alzheimer disease. Archives of Neurology, 62(12), 18701876.CrossRefGoogle ScholarPubMed
Capizzano, A.A., Acion, L., Bekinschtein, T., Furman, M., Gomila, H., Martinez, A., Starkstein, S.E. (2004). White matter hyperintensities are significantly associated with cortical atrophy in Alzheimer's disease. Journal of Neurology, Neurosurgery, & Psychiatry, 75(6), 822827.CrossRefGoogle ScholarPubMed
Choi, S.J., Lim, K.O., Monteiro, I., Reisberg, B. (2005). Diffusion tensor imaging of frontal white matter microstructure in early Alzheimer's disease: A preliminary study. Journal of Geriatric Psychiatry and Neurology, 18(1), 1219.Google Scholar
Cummings, J.L., Mega, M., Gray, K., Rosenberg-Thompson, S., Carusi, D.A. (1994). The neuropsychiatric inventory: Comprehensive assessment of psychopathology in dementia. Neurology, 44, 23082314.CrossRefGoogle ScholarPubMed
Damoiseaux, J.S., Smith, S.M., Witter, M.P., Sanz-Arigita, E.J., Barkhof, F., Scheltens, P., Rombouts, S.A. (2009). White matter tract integrity in aging and Alzheimer's disease. Human Brain Mapping, 30(4), 10511059.CrossRefGoogle ScholarPubMed
DeCarli, C., Miller, B.L., Swan, G.E., Reed, T., Wolf, P.A., Garner, J., Carmelli, D. (1999). Predictors of brain morphology for the men of the NHLBI twin study. Stroke, 30(3), 529536.CrossRefGoogle ScholarPubMed
DeCarli, C., Reed, B.R., Jagust, W., Martinez, O., Ortega, M., Mungas, D. (2008). Brain behavior relationships among African Americans, whites, and Hispanics. Alzheimer Disease and Associated Disorders, 22(4), 382391.CrossRefGoogle ScholarPubMed
Delano-Wood, L., Bondi, M.W., Sacco, J., Abeles, N., Jak, A.J., Libon, D.J., Bozoki, A. (2009). Heterogeneity in mild cognitive impairment: Differences in neuropsychological profile and associated white matter lesion pathology. Journal of the International Neuropsychological Society, 15(6), 906914.Google Scholar
Delis, D.C., Kramer, J.J., Kaplan, E., Ober, B.A. (2000). California verbal learning test (2nd ed.). San Antonio, TX: Psychological Corporation.Google Scholar
Duan, J.H., Wang, H.Q., Xu, J., Lin, X., Chen, S.Q., Kang, Z., Yao, Z.B. (2006). White matter damage of patients with Alzheimer's disease correlated with the decreased cognitive function. Surgical and Radiological Anatomy, 28(2), 150156.CrossRefGoogle ScholarPubMed
Dufouil, C., Alperovitch, A., Tzourio, C. (2003). Influence of education on the relationship between white matter lesions and cognition. Neurology, 60(5), 831836.CrossRefGoogle ScholarPubMed
Engelhardt, E., Moreira, D.M., Alves, G.S., Lanna, M.E., Alves, C.E., Ericeira-Valente, L., Laks, J. (2009). Binswanger's disease and quantitative fractional anisotropy. Arquivos de Neuro-psiquiatria, 67(2A), 179184.Google Scholar
Esiri, M.M., Wilcock, G.K. (1986). Cerebral amyloid angiopathy in dementia and old age. Journal of Neurology, Neurosurgery, & Psychiatry, 49(11), 12211226.CrossRefGoogle ScholarPubMed
Fazekas, F., Kleinert, R., Offenbacher, H., Schmidt, R., Kleinert, G., Payer, F., Lechner, H. (1993). Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology, 43(9), 16831689.CrossRefGoogle ScholarPubMed
Folstein, M.F., Folstein, S.E., McHugh, P.R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189198.CrossRefGoogle ScholarPubMed
Furutani, K., Harada, M., Minato, M., Morita, N., Nishitani, H. (2005). Regional changes of fractional anisotropy with normal aging using statistical parametric mapping (SPM). Journal of Investigative Medicine, 52(3-4), 186190.CrossRefGoogle ScholarPubMed
Goodglass, H., Kaplan, E. (1983). The Assessment of Aphasia and Related Disorders (2nd edition). Lea & Febiger, Philadelphia, PA.Google Scholar
Gootjes, L., Teipel, S.J., Zebuhr, Y., Schwarz, R., Leinsinger, G., Scheltens, P., Hampel, H. (2004). Regional distribution of white matter hyperintensities in vascular dementia, Alzheimer's disease and healthy aging. Dementia and Geriatric Cognitive Disorder, 18(2), 180188.CrossRefGoogle ScholarPubMed
Gouw, A.A., Seewann, A., van der Flier, W.M., Barkhof, F., Rozemuller, A.M., Scheltens, P., Geurts, J.J. (2011). Heterogeneity of small vessel disease: A systematic review of MRI and histopathology correlations. Journal of Neurology, Neurosurgery. & Psychiatry, 82(2), 126135. doi:jnnp.2009.204685 [pii] 10.1136/jnnp.2009.204685CrossRefGoogle ScholarPubMed
Grieve, S.M., Williams, L.M., Paul, R.H., Clark, C.R., Gordon, E. (2007). Cognitive aging, executive function, and fractional anisotropy: A diffusion tensor MR imaging study. AJNR American Journal of Neuroradiology, 28(2), 226235.Google ScholarPubMed
Gunning-Dixon, F.M., Raz, N. (2000). The cognitive correlates of white matter abnormalities in normal aging: A quantitative review. Neuropsychology, 14(2), 224232.CrossRefGoogle ScholarPubMed
Gurland, B.J., Wilder, D.E., Lantigua, R., Stern, Y., Chen, J., Killeffer, E.H., Mayeux, R. (1999). Rates of dementia in three ethnoracial groups. International Journal of Geriatric Psychiatry, 14(6), 481493.3.0.CO;2-5>CrossRefGoogle ScholarPubMed
Huang, J., Auchus, A.P. (2007). Diffusion tensor imaging of normal appearing white matter and its correlation with cognitive functioning in mild cognitive impairment and Alzheimer's disease. Annals of the New York Academy Science, 1097, 259264.CrossRefGoogle ScholarPubMed
Jenkinson, M., Bannister, P., Brady, M., Smith, S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage, 17(2), 825841.Google Scholar
Kaplan, E.F., Goodglass, H., Weintraub, S. (1983). The Boston Naming Test. Philadelphia, PA: Lippincott Williams & Wilkins.Google Scholar
Kiuchi, K., Morikawa, M., Taoka, T., Nagashima, T., Yamauchi, T., Makinodan, M., Kishimoto, T. (2009). Abnormalities of the uncinate fasciculus and posterior cingulate fasciculus in mild cognitive impairment and early Alzheimer's disease: A diffusion tensor tractography study. Brain Research, 1287, 184191. doi:S0006-8993(09)01268-2 [pii] 10.1016/j.brainres.2009.06.052CrossRefGoogle ScholarPubMed
Laakso, M.P., Soininen, H., Partanen, K., Helkala, E.L., Hartikainen, P., Vainio, P., Riekkinen, P.J. Sr., (1995). Volumes of hippocampus, amygdala and frontal lobes in the MRI-based diagnosis of early Alzheimer's disease: Correlation with memory functions. Journal of Neural Transmission, 9(1), 7386.Google Scholar
Leys, D., Pruvo, J.P., Parent, M., Vermersch, P., Soetaert, G., Steinling, M., Clarisse, J. (1991). Could Wallerian degeneration contribute to “leuko-araiosis” in subjects free of any vascular disorder? Journal of Neurology, Neurosurgery, & Psychiatry, 54(1), 4650.CrossRefGoogle ScholarPubMed
Liao, D., Cooper, L., Cai, J., Toole, J., Bryan, N., Burke, G., Heiss, G. (1997). The prevalence and severity of white matter lesions, their relationship with age, ethnicity, gender, and cardiovascular disease risk factors: The ARIC Study. Neuroepidemiology, 16(3), 149162.Google Scholar
Liao, D., Cooper, L., Cai, J., Toole, J.F., Bryan, N.R., Hutchinson, R.G., Tyroler, H.A. (1996). Presence and severity of cerebral white matter lesions and hypertension, its treatment, and its control. The ARIC Study. Atherosclerosis Risk in Communities Study. Stroke, 27(12), 22622270.CrossRefGoogle ScholarPubMed
Liu, Y., Spulber, G., Lehtimaki, K.K., Kononen, M., Hallikainen, I., Grohn, H., Soininen, H. (2011). Diffusion tensor imaging and Tract-Based Spatial Statistics in Alzheimer's disease and mild cognitive impairment. Neurobiology of Aging, 32(9), 15581571. doi:S0197-4580(09)00336-4 [pii] 10.1016/j.neurobiolaging.2009.10.006CrossRefGoogle ScholarPubMed
Luchsinger, J.A., Brickman, A.M., Reitz, C., Cho, S.J., Schupf, N., Manly, J.J., Brown, T.R. (2009). Subclinical cerebrovascular disease in mild cognitive impairment. Neurology, 73(6), 450456.CrossRefGoogle ScholarPubMed
Madden, D.J., Bennett, I.J., Song, A.W. (2009). Cerebral white matter integrity and cognitive aging: Contributions from diffusion tensor imaging. Neuropsychology Review, 19(4), 415435.Google Scholar
Manolio, T.A., Kronmal, R.A., Burke, G.L., Poirier, V., O'Leary, D.H., Gardin, J.M., Bryan, R.N. (1994). Magnetic resonance abnormalities and cardiovascular disease in older adults. The Cardiovascular Health Study. Stroke, 25(2), 318327.CrossRefGoogle ScholarPubMed
Matsuda, H. (2001). Cerebral blood flow and metabolic abnormalities in Alzheimer's disease. Annals of Nuclear Medicine, 15(2), 8592.Google Scholar
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., Stadlan, E. (1984). Clinical diagnosis of Alzheimer's disease: Report of the NINCDS-ADRDA Work Group under the auspices of the Department of Health and Human Services Task Force on Alzheimer's disease. Neurology, 34, 939944.CrossRefGoogle ScholarPubMed
Medina, D., DeToledo-Morrell, L., Urresta, F., Gabrieli, J.D., Moseley, M., Fleischman, D., Stebbins, G.T. (2006). White matter changes in mild cognitive impairment and AD: A diffusion tensor imaging study. Neurobiology of Aging, 27(5), 663672.CrossRefGoogle Scholar
Meyer, J.S., Rauch, G.M., Crawford, K., Rauch, R.A., Konno, S., Akiyama, H., Haque, A. (1999). Risk factors accelerating cerebral degenerative changes, cognitive decline and dementia. International Journal of Geriatric Psychiatry, 14(12), 10501061.3.0.CO;2-Z>CrossRefGoogle ScholarPubMed
Mori, S., Barker, P.B. (1999). Diffusion magnetic resonance imaging: Its principle and applications. The Anatomical Record, 257(3), 102109.Google Scholar
Mori, S., Crain, B.J., Chacko, V.P., van Zijl, P.C. (1999). Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Annals of Neurology, 45(2), 265269.3.0.CO;2-3>CrossRefGoogle ScholarPubMed
Morris, J.C., Heyman, A., Mohs, R.C., Hughes, J.P., van Belle, G., Fillenbaum, G., Clark, C. (1989). The consortium to establish a registry for Alzheimer's disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer's disease. Neurology, 39, 11591165.Google Scholar
Naggara, O., Oppenheim, C., Rieu, D., Raoux, N., Rodrigo, S., Dalla Barba, G., Meder, J.F. (2006). Diffusion tensor imaging in early Alzheimer's disease. Psychiatry Rsearch, 146(3), 243249.Google Scholar
Oliveira, A.P., Brickman, A.M., Provenzano, F.A., Muraskin, J., Louis, E.D. (in press). White matter hyperintensity burden on magnetic resonance imaging in essential tremor: A population-based study in New York. Tremor and Other Hyperkinetic Movements.Google Scholar
Osterrieth, P.A. (1944). Filetest de copie d'une figure complex: Contribution a l'etude de la perception et de la memoire. Archives de Psychologie, 30, 286356.Google Scholar
Penke, L., Deary, I.J. (2010). Some guidelines for structural equation modelling in cognitive neuroscience: The case of Charlton et al.'s study on white matter integrity and cognitive ageing. Neurobiology of Aging, 31(9), 16561660; discussion 1561–1656.CrossRefGoogle Scholar
Penke, L., Munoz Maniega, S., Murray, C., Gow, A.J., Hernandez, M.C., Clayden, J.D., Deary, I.J. (2010). A general factor of brain white matter integrity predicts information processing speed in healthy older people. Journal of Neuroscience, 30(22), 75697574.Google Scholar
Perkins, N.J., Schisterman, E.F. (2006). The inconsistency of “optimal” cutpoints obtained using two criteria based on the receiver operating characteristic curve. American Journal of Epidemiology, 163(7), 670675.Google Scholar
Petersen, R.C., Smith, G.E., Waring, S.C., Ivnik, R.J., Tangalos, E.G., Kokmen, E. (1999). Mild cognitive impairment: Clinical characterization and outcome. Archives of Neurology, 56, 303308.CrossRefGoogle ScholarPubMed
Pfeffer, R.I., Kurosaki, C.H., Harrah, C.H., Chance, J.M., Filos, S. (1982). Measurement of functional activities in older adults in the community. Journal of Gerontology, 37, 323329.Google Scholar
Pierpaoli, C., Basser, P.J. (1996). Toward a quantitative assessment of diffusion anisotropy. Magnetic Resonance in Medicine, 36(6), 893906.CrossRefGoogle Scholar
Pievani, M., Agosta, F., Pagani, E., Canu, E., Sala, S., Absinta, M., Filippi, M. (2010). Assessment of white matter tract damage in mild cognitive impairment and Alzheimer's disease. Human Brain Mapping, 31(12), 18621875. doi:10.1002/hbm.20978.Google Scholar
Raz, N., Rodrigue, K.M., Kennedy, K.M., Acker, J.D. (2007). Vascular health and longitudinal changes in brain and cognition in middle-aged and older adults. Neuropsychology, 21(2), 149157.CrossRefGoogle ScholarPubMed
Reitan, R. (1978). Manual for Administration of Neuropsychological Test Batteries for Adults and Children. Reitan Neuropsychology Laboratories, Inc. Tucson, AZ.Google Scholar
Reitz, C., Schupf, N., Luchsinger, J.A., Brickman, A.M., Manly, J.J., Andrews, H., Mayeux, R. (2009). Validity of self-reported stroke in elderly African Americans, Caribbean Hispanics, and Whites. Archives of Neurology, 66(7), 834840.CrossRefGoogle ScholarPubMed
Ringman, J.M., O'Neill, J., Geschwind, D., Medina, L., Apostolova, L.G., Rodriguez, Y., Bartzokis, G. (2007). Diffusion tensor imaging in preclinical and presymptomatic carriers of familial Alzheimer's disease mutations. Brain, 130(Pt 7), 17671776.CrossRefGoogle ScholarPubMed
Rose, S.E., Janke, A.L., Chalk, J.B. (2008). Gray and white matter changes in Alzheimer's disease: A diffusion tensor imaging study. Journal of Magnetic Resonance Imaging, 27(1), 2026.CrossRefGoogle ScholarPubMed
Salat, D.H., Tuch, D.S., Greve, D.N., van der Kouwe, A.J., Hevelone, N.D., Zaleta, A.K., Dale, A.M. (2005). Age-related alterations in white matter microstructure measured by diffusion tensor imaging. Neurobiology of Aging, 26(8), 12151227.CrossRefGoogle ScholarPubMed
Sano, M., Stern, Y., Mayeux, R., Hartman, S., Devanand, D.P. (1987). A standardized technique for establishing the onset symptoms of probable Alzheimer's disease. Journal of Clinical and Experimental Neuropsychology, 9, 6565.Google Scholar
Scheltens, P., Barkhof, F., Valk, J., Algra, P.R., van der Hoop, R.G., Nauta, J., Wolters, E.C. (1992). White matter lesions on magnetic resonance imaging in clinically diagnosed Alzheimer's disease. Evidence for heterogeneity. Brain, 115 Pt (3), 735748.CrossRefGoogle ScholarPubMed
Smith, C.D., Snowdon, D.A., Wang, H., Markesbery, W.R. (2000). White matter volumes and periventricular white matter hyperintensities in aging and dementia. Neurology, 54(4), 838842.CrossRefGoogle ScholarPubMed
Smith, E.E., Egorova, S., Blacker, D., Killiany, R.J., Muzikansky, A., Dickerson, B.C., Guttmann, C.R. (2008). Magnetic resonance imaging white matter hyperintensities and brain volume in the prediction of mild cognitive impairment and dementia. Archives of Neurology, 65(1), 94100.CrossRefGoogle ScholarPubMed
Smith, E.E., Salat, D.H., Jeng, J., McCreary, C.R., Fischl, B., Schmahmann, J.D., Greenberg, S.M. (2011). Correlations between MRI white matter lesion location and executive function and episodic memory. Neurology, 76(17), 14921499.CrossRefGoogle ScholarPubMed
Smith, S.M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T.E., Mackay, C.E., Behrens, T.E. (2006). Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. Neuroimage, 31(4), 14871505.Google Scholar
Smith, S.M., Jenkinson, M., Woolrich, M.W., Beckmann, C.F., Behrens, T.E., Johansen-Berg, H., Matthews, P.M. (2004). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage, 23(Suppl 1), S208S219.Google Scholar
Strassburger, T.L., Lee, H.C., Daly, E.M., Szczepanik, J., Krasuski, J.S., Mentis, M.J., Alexander, G.E. (1997). Interactive effects of age and hypertension on volumes of brain structures. Stroke, 28(7), 14101417.Google Scholar
Stricker, N.H., Schweinsburg, B.C., Delano-Wood, L., Wierenga, C.E., Bangen, K.J., Haaland, K.Y., Bondi, M.W. (2009). Decreased white matter integrity in late-myelinating fiber pathways in Alzheimer's disease supports retrogenesis. Neuroimage, 45(1), 1016.Google Scholar
Takahashi, S., Yonezawa, H., Takahashi, J., Kudo, M., Inoue, T., Tohgi, H. (2002). Selective reduction of diffusion anisotropy in white matter of Alzheimer disease brains measured by 3.0 Tesla magnetic resonance imaging. Neuroscience Letters, 332(1), 4548.CrossRefGoogle ScholarPubMed
Tanabe, J.L., Amend, D., Schuff, N., DiSclafani, V., Ezekiel, F., Norman, D., Weiner, M.W. (1997). Tissue segmentation of the brain in Alzheimer disease. AJNR American Journal of Neuroradiology, 18(1), 115123.Google ScholarPubMed
Tang, M.X., Cross, P., Andrews, H., Jacobs, D.M., Small, S., Bell, K., Mayeux, R. (2001). Incidence of AD in African-Americans, Caribbean Hispanics, and Caucasians in northern Manhattan. Neurology, 56(1), 4956.CrossRefGoogle ScholarPubMed
Taylor, W.D., Payne, M.E., Krishnan, K.R., Wagner, H.R., Provenzale, J.M., Steffens, D.C., MacFall, J.R. (2001). Evidence of white matter tract disruption in MRI hyperintensities. Biological Psychiatry, 50(3), 179183.Google Scholar
Unverzagt, F.W., Hall, K.S., Torke, A.M., Rediger, J.D. (1996). Effects of age, education and gender on CERAD neuropsychological test performance in an African American sample. Clinical Neuropsychology, 10, 180190.Google Scholar
Vernooij, M.W., Ikram, M.A., Vrooman, H.A., Wielopolski, P.A., Krestin, G.P., Hofman, A., Breteler, M.M. (2009). White matter microstructural integrity and cognitive function in a general elderly population. Archives of General Psychiatry, 66(5), 545553.CrossRefGoogle Scholar
Viswanathan, A., Rocca, W.A., Tzourio, C. (2009). Vascular risk factors and dementia: How to move forward? Neurology, 72(4), 368374.Google Scholar
Wahl, M., Li, Y.O., Ng, J., Lahue, S.C., Cooper, S.R., Sherr, E.H., Mukherjee, P. (2010). Microstructural correlations of white matter tracts in the human brain. Neuroimage, 51(2), 531541.Google Scholar
Wechsler, D. (1997). WMS-III administration and scoring manual. San Antonio, TX: Psychological Corporation.Google Scholar
Weintraub, S., Salmon, D., Mercaldo, N., Ferris, S., Graff-Radford, N.R., Chui, H., Morris, J.C. (2009). The Alzheimer's Disease Centers’ Uniform Data Set (UDS): The neuropsychologic test battery. Alzheimer Disease and Associated Discorders, 23(2), 91101.Google Scholar
Xie, S., Xiao, J.X., Gong, G.L., Zang, Y.F., Wang, Y.H., Wu, H.K., Jiang, X.X. (2006). Voxel-based detection of white matter abnormalities in mild Alzheimer disease. Neurology, 66(12), 18451849.Google Scholar
Yoshita, M., Fletcher, E., Harvey, D., Ortega, M., Martinez, O., Mungas, D.M., DeCarli, C.S. (2006). Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD. Neurology, 67(12), 21922198.CrossRefGoogle ScholarPubMed
Yoshiura, T., Mihara, F., Ogomori, K., Tanaka, A., Kaneko, K., Masuda, K. (2002). Diffusion tensor in posterior cingulate gyrus: Correlation with cognitive decline in Alzheimer's disease. Neuroreport, 13(17), 22992302.Google Scholar