546
Views
56
CrossRef citations to date
0
Altmetric
Theme: Alzheimer’s Disease - Review

White matter abnormalities associated with Alzheimer’s disease and mild cognitive impairment: a critical review of MRI studies

, , , , , & show all
Pages 483-493 | Published online: 09 Jan 2014

References

  • Dubois B, Feldman HH, Jacova C et al. Revising the definition of Alzheimer’s disease: a new lexicon. Lancet Neurol. 9(11), 1118–1127 (2010).
  • Sperling RA, Aisen PS, Beckett LA et al. Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging – Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 7(3), 280–292 (2011).
  • Dickerson BC, Sperling RA. Neuroimaging biomarkers for clinical trials of disease-modifying therapies in Alzheimer’s disease. NeuroRx 2(2), 348–360 (2005).
  • Hommet C, Mondon K, Constans T et al. Review of cerebral microangiopathy and Alzheimer’s disease: relation between white matter hyperintensities and microbleeds. Dement. Geriatr. Cogn. Disord. 32(6), 367–378 (2011).
  • Admiraal-Behloul F, van den Heuvel DM, Olofsen H et al. Fully automatic segmentation of white matter hyperintensities in MR images of the elderly. Neuroimage 28(3), 607–617 (2005).
  • Gold BT, Powell DK, Andersen AH, Smith CD. Alterations in multiple measures of white matter integrity in normal women at high risk for Alzheimer’s disease. Neuroimage 52(4), 1487–1494 (2010).
  • Longstreth WT Jr, Manolio TA, Arnold A et al. Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people. The Cardiovascular Health Study. Stroke 27(8), 1274–1282 (1996).
  • Schmidt R, Schmidt H, Haybaeck J et al. Heterogeneity in age-related white matter changes. Acta Neuropathol. 122(2), 171–185 (2011).
  • Fazekas F, Chawluk JB, Alavi A, Hurtig HI, Zimmerman RA. MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR. Am. J. Roentgenol. 149(2), 351–356 (1987).
  • Wahlund LO, Barkhof F, Fazekas F et al.; European Task Force on Age-Related White Matter Changes. A new rating scale for age-related white matter changes applicable to MRI and CT. Stroke 32(6), 1318–1322 (2001).
  • Brickman AM, Sneed JR, Provenzano FA et al. Quantitative approaches for assessment of white matter hyperintensities in elderly populations. Psychiatry Res. 193(2), 101–106 (2011).
  • Rostrup E, Gouw AA, Vrenken H et al.; LADIS study group. The spatial distribution of age-related white matter changes as a function of vascular risk factors – results from the LADIS study. Neuroimage 60(3), 1597–1607 (2012).
  • Gouw AA, Seewann A, van der Flier WM et al. Heterogeneity of small vessel disease: a systematic review of MRI and histopathology correlations. J. Neurol. Neurosurg. Psychiatr. 82(2), 126–135 (2011).
  • Simpson JE, Fernando MS, Clark L et al.; MRC Cognitive Function and Ageing Neuropathology Study Group. White matter lesions in an unselected cohort of the elderly: astrocytic, microglial and oligodendrocyte precursor cell responses. Neuropathol. Appl. Neurobiol. 33(4), 410–419 (2007).
  • Simpson JE, Ince PG, Higham CE et al.; MRC Cognitive Function and Ageing Neuropathology Study Group. Microglial activation in white matter lesions and nonlesional white matter of ageing brains. Neuropathol. Appl. Neurobiol. 33(6), 670–683 (2007).
  • Elias MF, Elias PK, Sullivan LM, Wolf PA, D’Agostino RB. Lower cognitive function in the presence of obesity and hypertension: the Framingham heart study. Int. J. Obes. Relat. Metab. Disord. 27(2), 260–268 (2003).
  • de la Torre JC. Three postulates to help identify the cause of Alzheimer’s disease. J. Alzheimers Dis. 24(4), 657–668 (2011).
  • O’Brien JT, Erkinjuntti T, Reisberg B et al. Vascular cognitive impairment. Lancet Neurol. 2(2), 89–98 (2003).
  • Hachinski VC, Iliff LD, Zilhka E et al. Cerebral blood flow in dementia. Arch. Neurol. 32(9), 632–637 (1975).
  • Loeb C, Gandolfo C. Diagnostic evaluation of degenerative and vascular dementia. Stroke 14(3), 399–401 (1983).
  • Rosen WG, Terry RD, Fuld PA, Katzman R, Peck A. Pathological verification of ischemic score in differentiation of dementias. Ann. Neurol. 7(5), 486–488 (1980).
  • Moroney JT, Bagiella E, Desmond DW et al. Meta-analysis of the Hachinski Ischemic Score in pathologically verified dementias. Neurology 49(4), 1096–1105 (1997).
  • Brewster PW, McDowell I, Moineddin R, Tierney MC. Differential prediction of vascular dementia and Alzheimer’s disease in nondemented older adults within 5 years of initial testing. Alzheimers. Dement. 8(6), 528–535 (2012).
  • Gunning-Dixon FM, Raz N. The cognitive correlates of white matter abnormalities in normal aging: a quantitative review. Neuropsychology 14(2), 224–232 (2000).
  • Hedden T, Mormino EC, Amariglio RE et al. Cognitive profile of amyloid burden and white matter hyperintensities in cognitively normal older adults. J. Neurosci. 32(46), 16233–16242 (2012).
  • Herrmann LL, Le Masurier M, Ebmeier KP. White matter hyperintensities in late life depression: a systematic review. J. Neurol. Neurosurg. Psychiatr. 79(6), 619–624 (2008).
  • Tamashiro JH, Zung S, Zanetti MV et al. Increased rates of white matter hyperintensities in late-onset bipolar disorder. Bipolar Disord. 10(7), 765–775 (2008).
  • Marchant NL, Reed BR, Sanossian N et al. The aging brain and cognition: contribution of vascular injury and Aβ to mild cognitive dysfunction. JAMA Neurol. 70(4), 488–495 (2013).
  • Wahlund LO, Almkvist O, Basun H, Julin P. MRI in successful aging, a 5-year follow-up study from the eighth to ninth decade of life. Magn. Reson. Imaging 14(6), 601–608 (1996).
  • Murray ME, Senjem ML, Petersen RC et al. Functional impact of white matter hyperintensities in cognitively normal elderly subjects. Arch. Neurol. 67(11), 1379–1385 (2010).
  • Hardy J, Selkoe DJ. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science 297(5580), 353–356 (2002).
  • Braak H, Braak E. Frequency of stages of Alzheimer-related lesions in different age categories. Neurobiol. Aging 18(4), 351–357 (1997).
  • Price JL, Morris JC. Tangles and plaques in nondemented aging and ‘preclinical’ Alzheimer’s disease. Ann. Neurol. 45(3), 358–368 (1999).
  • Ferreira LK, Busatto GF. Neuroimaging in Alzheimer’s disease: current role in clinical practice and potential future applications. Clinics (Sao. Paulo). 66(Suppl. 1), 19–24 (2011).
  • Provenzano FA, Muraskin J, Tosto G et al.; for the Alzheimer’s Disease Neuroimaging Initiative. White matter hyperintensities and cerebral amyloidosis: necessary and sufficient for clinical expression of Alzheimer disease? JAMA Neurol. 70(4), 455–461 (2013).
  • Carmichael O, Schwarz C, Drucker D et al.; Alzheimer’s Disease Neuroimaging Initiative. Longitudinal changes in white matter disease and cognition in the first year of the Alzheimer disease neuroimaging initiative. Arch. Neurol. 67(11), 1370–1378 (2010).
  • Brickman AM, Provenzano FA, Muraskin J et al. Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community. Arch. Neurol. 69(12), 1621–1627 (2012).
  • Gorelick PB, Scuteri A, Black SE et al.; American Heart Association Stroke Council, Council on Epidemiology and Prevention, Council on Cardiovascular Nursing, Council on Cardiovascular Radiology and Intervention, and Council on Cardiovascular Surgery and Anesthesia. Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 42(9), 2672–2713 (2011).
  • Debette S, Markus HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 341, c3666 (2010).
  • Mechelli A, Price CJ, Friston KJ, Ashburner J. Voxel-based morphometry of the human brain: methods and applications. Curr. Med. Imag. Rev. 1(2), 105–113 (2005).
  • Busatto GF, Diniz BS, Zanetti MV. Voxel-based morphometry in Alzheimer’s disease. Expert Rev. Neurother. 8(11), 1691–1702 (2008).
  • Whitwell JL. Voxel-based morphometry: an automated technique for assessing structural changes in the brain. J. Neurosci. 29(31), 9661–9664 (2009).
  • Chaim TM, Duran FL, Uchida RR, Périco CA, de Castro CC, Busatto GF. Volumetric reduction of the corpus callosum in Alzheimer’s disease in vivo as assessed with voxel-based morphometry. Psychiatry Res. 154(1), 59–68 (2007).
  • Balthazar ML, Yasuda CL, Pereira FR, Pedro T, Damasceno BP, Cendes F. Differences in grey and white matter atrophy in amnestic mild cognitive impairment and mild Alzheimer’s disease. Eur. J. Neurol. 16(4), 468–474 (2009).
  • Busatto GF, Garrido GE, Almeida OP et al. A voxel-based morphometry study of temporal lobe gray matter reductions in Alzheimer’s disease. Neurobiol. Aging 24(2), 221–231 (2003).
  • Balthazar ML, Yasuda CL, Cendes F, Damasceno BP. Learning, retrieval, and recognition are compromised in aMCI and mild AD: are distinct episodic memory processes mediated by the same anatomical structures? J. Int. Neuropsychol. Soc. 16(1), 205–209 (2010).
  • Ferreira LK, Diniz BS, Forlenza OV, Busatto GF, Zanetti MV. Neurostructural predictors of Alzheimer’s disease: a meta-analysis of VBM studies. Neurobiol. Aging 32(10), 1733–1741 (2011).
  • Li J, Pan P, Huang R, Shang H. A meta-analysis of voxel-based morphometry studies of white matter volume alterations in Alzheimer’s disease. Neurosci. Biobehav. Rev. 36(2), 757–763 (2012).
  • Di Paola M, Luders E, Di Iulio F et al. Callosal atrophy in mild cognitive impairment and Alzheimer’s disease: different effects in different stages. Neuroimage 49(1), 141–149 (2010).
  • Hampel H, Teipel SJ, Alexander GE, Pogarell O, Rapoport SI, Möller HJ. In vivo imaging of region and cell type specific neocortical neurodegeneration in Alzheimer’s disease. Perspectives of MRI derived corpus callosum measurement for mapping disease progression and effects of therapy. Evidence from studies with MRI, EEG and PET. J. Neural Transm. 109(5–6), 837–855 (2002).
  • Teipel SJ, Bayer W, Alexander GE et al. Regional pattern of hippocampus and corpus callosum atrophy in Alzheimer’s disease in relation to dementia severity: evidence for early neocortical degeneration. Neurobiol. Aging 24(1), 85–94 (2003).
  • Teipel SJ, Bayer W, Alexander GE et al. Progression of corpus callosum atrophy in Alzheimer disease. Arch. Neurol. 59(2), 243–248 (2002).
  • Li S, Pu F, Shi F, Xie S, Wang Y, Jiang T. Regional white matter decreases in Alzheimer’s disease using optimized voxel-based morphometry. Acta Radiol. 49(1), 84–90 (2008).
  • Matsuda H. Voxel-based morphometry of brain MRI in normal aging and Alzheimer’s disease. Aging Dis. 4(1), 29–37 (2013).
  • Di Paola M, Spalletta G, Caltagirone C. In vivo structural neuroanatomy of corpus callosum in Alzheimer’s disease and mild cognitive impairment using different MRI techniques: a review. J. Alzheimers Dis. 20(1), 67–95 (2010).
  • Stoub TR, deToledo-Morrell L, Stebbins GT, Leurgans S, Bennett DA, Shah RC. Hippocampal disconnection contributes to memory dysfunction in individuals at risk for Alzheimer’s disease. Proc. Natl Acad. Sci. USA 103(26), 10041–10045 (2006).
  • Guo X, Wang Z, Li K et al. Voxel-based assessment of gray and white matter volumes in Alzheimer’s disease. Neurosci. Lett. 468(2), 146–150 (2010).
  • Villain N, Desgranges B, Viader F et al. Relationships between hippocampal atrophy, white matter disruption, and gray matter hypometabolism in Alzheimer’s disease. J. Neurosci. 28(24), 6174–6181 (2008).
  • Pereira JM, Xiong L, Acosta-Cabronero J, Pengas G, Williams GB, Nestor PJ. Registration accuracy for VBM studies varies according to region and degenerative disease grouping. Neuroimage 49(3), 2205–2215 (2010).
  • Davatzikos C, Vaillant M, Resnick SM, Prince JL, Letovsky S, Bryan RN. A computerized approach for morphological analysis of the corpus callosum. J. Comput. Assist. Tomogr. 20(1), 88–97 (1996).
  • Leporé N, Brun C, Pennec X et al. Mean template for tensor-based morphometry using deformation tensors. Med. Image Comput. Comput. Assist. Interv. 10(Pt 2), 826–833 (2007).
  • Friese U, Meindl T, Herpertz SC, Reiser MF, Hampel H, Teipel SJ. Diagnostic utility of novel MRI-based biomarkers for Alzheimer’s disease: diffusion tensor imaging and deformation-based morphometry. J. Alzheimers Dis. 20(2), 477–490 (2010).
  • Fischl B. FreeSurfer. Neuroimage 62(2), 774–781 (2012).
  • Westman E, Muehlboeck JS, Simmons A. Combining MRI and CSF measures for classification of Alzheimer’s disease and prediction of mild cognitive impairment conversion. Neuroimage 62(1), 229–238 (2012).
  • Ridgway GR, Lehmann M, Barnes J et al. Early-onset Alzheimer disease clinical variants: multivariate analyses of cortical thickness. Neurology 79(1), 80–84 (2012).
  • Salat DH, Greve DN, Pacheco JL et al. Regional white matter volume differences in nondemented aging and Alzheimer’s disease. Neuroimage 44(4), 1247–1258 (2009).
  • Clarkson MJ, Cardoso MJ, Ridgway GR et al. A comparison of voxel and surface based cortical thickness estimation methods. Neuroimage 57(3), 856–865 (2011).
  • Masutani Y, Aoki S, Abe O, Hayashi N, Otomo K. MR diffusion tensor imaging: recent advance and new techniques for diffusion tensor visualization. Eur. J. Radiol. 46(1), 53–66 (2003).
  • Yoon B, Shim YS, Hong YJ et al. Comparison of diffusion tensor imaging and voxel-based morphometry to detect white matter damage in Alzheimer’s disease. J. Neurol. Sci. 302(1–2), 89–95 (2011).
  • Sydykova D, Stahl R, Dietrich O et al. Fiber connections between the cerebral cortex and the corpus callosum in Alzheimer’s disease: a diffusion tensor imaging and voxel-based morphometry study. Cereb. Cortex 17(10), 2276–2282 (2007).
  • Mielke MM, Kozauer NA, Chan KC et al. Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer’s disease. Neuroimage 46(1), 47–55 (2009).
  • Cho H, Yang DW, Shon YM et al. Abnormal integrity of corticocortical tracts in mild cognitive impairment: a diffusion tensor imaging study. J. Korean Med. Sci. 23(3), 477–483 (2008).
  • Salat DH, Tuch DS, van der Kouwe AJ et al. White matter pathology isolates the hippocampal formation in Alzheimer’s disease. Neurobiol. Aging 31(2), 244–256 (2010).
  • O’Dwyer L, Lamberton F, Bokde AL et al. Multiple indices of diffusion identifies white matter damage in mild cognitive impairment and Alzheimer’s disease. PLoS ONE 6(6), e21745 (2011).
  • Alves GS, O’Dwyer L, Jurcoane A et al. Different patterns of white matter degeneration using multiple diffusion indices and volumetric data in mild cognitive impairment and Alzheimer patients. PLoS ONE 7(12), e52859 (2012).
  • Stricker NH, Schweinsburg BC, Delano-Wood L et al. Decreased white matter integrity in late-myelinating fiber pathways in Alzheimer’s disease supports retrogenesis. Neuroimage 45(1), 10–16 (2009).
  • Sexton CE, Kalu UG, Filippini N, Mackay CE, Ebmeier KP. A meta-analysis of diffusion tensor imaging in mild cognitive impairment and Alzheimer’s disease. Neurobiol. Aging 32(12), 2322.e5–2322.18 (2011).
  • Clerx L, Visser PJ, Verhey F, Aalten P. New MRI markers for Alzheimer’s disease: a meta-analysis of diffusion tensor imaging and a comparison with medial temporal lobe measurements. J. Alzheimers Dis. 29(2), 405–429 (2012).
  • Shu N, Wang Z, Qi Z, Li K, He Y. Multiple diffusion indices reveals white matter degeneration in Alzheimer’s disease and mild cognitive impairment: a tract-based spatial statistics study. J. Alzheimers Dis. 26(Suppl. 3), 275–285 (2011).
  • Mielke MM, Okonkwo OC, Oishi K et al. Fornix integrity and hippocampal volume predict memory decline and progression to Alzheimer’s disease. Alzheimers. Dement. 8(2), 105–113 (2012).
  • Kalus P, Slotboom J, Gallinat J et al. Examining the gateway to the limbic system with diffusion tensor imaging: the perforant pathway in dementia. Neuroimage 30(3), 713–720 (2006).
  • Wang J, Zuo X, Dai Z et al. Disrupted functional brain connectome in individuals at risk for Alzheimer’s disease. Biol. Psychiatr. 73(5), 472–481. (2012).
  • Heinemann U, Schmitz D, Eder C, Gloveli T. Properties of entorhinal cortex projection cells to the hippocampal formation. Ann. N. Y. Acad. Sci. 911, 112–126 (2000).
  • Witter MP. The perforant path: projections from the entorhinal cortex to the dentate gyrus. Prog. Brain Res. 163, 43–61 (2007).
  • Hyman BT, Van Hoesen GW, Kromer LJ, Damasio AR. Perforant pathway changes and the memory impairment of Alzheimer’s disease. Ann. Neurol. 20(4), 472–481 (1986).
  • Morys J, Sadowski M, Barcikowska M, Maciejewska B, Narkiewicz O. The second layer neurones of the entorhinal cortex and the perforant path in physiological ageing and Alzheimer’s disease. Acta Neurobiol. Exp. (Wars) 54(1), 47–53 (1994).
  • Xie S, Xiao JX, Gong GL et al. Voxel-based detection of white matter abnormalities in mild Alzheimer disease. Neurology 66(12), 1845–1849 (2006).
  • Smith SM, Jenkinson M, Johansen-Berg H et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31(4), 1487–1505 (2006).
  • van Bruggen T, Stieltjes B, Thomann PA, Parzer P, Meinzer HP, Fritzsche KH. Do Alzheimer-specific microstructural changes in mild cognitive impairment predict conversion? Psychiatry Res. 203(2–3), 184–193 (2012).
  • Zhuang L, Wen W, Zhu W et al. White matter integrity in mild cognitive impairment: a tract-based spatial statistics study. Neuroimage 53(1), 16–25 (2010).
  • Liu Y, Spulber G, Lehtimäki KK et al. Diffusion tensor imaging and tract-based spatial statistics in Alzheimer’s disease and mild cognitive impairment. Neurobiol. Aging 32(9), 1558–1571 (2011).
  • Jones DK, Knösche TR, Turner R. White matter integrity, fiber count, and other fallacies: the do’s and don’ts of diffusion MRI. Neuroimage 73, 239–254 (2013).
  • Oishi K, Mielke MM, Albert M, Lyketsos CG, Mori S. DTI analyses and clinical applications in Alzheimer’s disease. J. Alzheimers Dis. 26(Suppl. 3), 287–296 (2011).
  • Takahashi M, Hackney DB, Zhang G et al. Magnetic resonance microimaging of intraaxonal water diffusion in live excised lamprey spinal cord. Proc. Natl Acad. Sci. USA 99(25), 16192–16196 (2002).
  • Lyketsos CG, Carrillo MC, Ryan JM et al. Neuropsychiatric symptoms in Alzheimer’s disease. Alzheimers. Dement. 7(5), 532–539 (2011).
  • Bruen PD, McGeown WJ, Shanks MF, Venneri A. Neuroanatomical correlates of neuropsychiatric symptoms in Alzheimer’s disease. Brain 131(Pt 9), 2455–2463 (2008).
  • Trzepacz PT, Yu P, Bhamidipati PK et al.; Alzheimer’s Disease Neuroimaging Initiative. Frontolimbic atrophy is associated with agitation and aggression in mild cognitive impairment and Alzheimer’s disease. Alzheimers. Dement. doi:10.1016/j.jalz.2012.10.005 (2012) (Epub ahead of print).
  • Nakaaki S, Sato J, Torii K et al. Neuroanatomical abnormalities before onset of delusions in patients with Alzheimer’s disease: a voxel-based morphometry study. Neuropsychiatr. Dis. Treat. 9, 1–8 (2013).
  • Tighe SK, Oishi K, Mori S et al. Diffusion tensor imaging of neuropsychiatric symptoms in mild cognitive impairment and Alzheimer’s dementia. J. Neuropsychiatry Clin. Neurosci. 24(4), 484–488 (2012).
  • Ota M, Sato N, Nakata Y, Arima K, Uno M. Relationship between apathy and diffusion tensor imaging metrics of the brain in Alzheimer’s disease. Int. J. Geriatr. Psychiatry 27(7), 722–726 (2012).
  • Tomimoto H, Lin JX, Matsuo A et al. Different mechanisms of corpus callosum atrophy in Alzheimer’s disease and vascular dementia. J. Neurol. 251(4), 398–406 (2004).
  • Bartzokis G. Alzheimer’s disease as homeostatic responses to age-related myelin breakdown. Neurobiol. Aging 32(8), 1341–1371 (2011).
  • Brickman AM, Meier IB, Korgaonkar MS et al. Testing the white matter retrogenesis hypothesis of cognitive aging. Neurobiol. Aging 33(8), 1699–1715 (2012).
  • Bartzokis G. Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease. Neurobiol. Aging 25(1), 5–18; author reply 49 (2004).
  • Kuceyeski A, Zhang Y, Raj A. Linking white matter integrity loss to associated cortical regions using structural connectivity information in Alzheimer’s disease and fronto-temporal dementia: the Loss in Connectivity (LoCo) score. Neuroimage 61(4), 1311–1323 (2012).
  • Fu JL, Zhang T, Chang C, Zhang YZ, Li WB. The value of diffusion tensor imaging in the differential diagnosis of subcortical ischemic vascular dementia and Alzheimer’s disease in patients with only mild white matter alterations on T2-weighted images. Acta Radiol. 53(3), 312–317 (2012).
  • Bozoki AC, Korolev IO, Davis NC, Hoisington LA, Berger KL. Disruption of limbic white matter pathways in mild cognitive impairment and Alzheimer’s disease: a DTI/FDG-PET study. Hum. Brain Mapp. 33(8), 1792–1802 (2012).
  • Müller MJ, Greverus D, Weibrich C et al. Diagnostic utility of hippocampal size and mean diffusivity in amnestic MCI. Neurobiol. Aging 28(3), 398–403 (2007).
  • O’Dwyer L, Lamberton F, Bokde AL et al. Using support vector machines with multiple indices of diffusion for automated classification of mild cognitive impairment. PLoS ONE 7(2), e32441 (2012).
  • Wang L, Goldstein FC, Veledar E et al. Alterations in cortical thickness and white matter integrity in mild cognitive impairment measured by whole-brain cortical thickness mapping and diffusion tensor imaging. AJNR. Am. J. Neuroradiol. 30(5), 893–899 (2009).
  • McMillan CT, Brun C, Siddiqui S et al. White matter imaging contributes to the multimodal diagnosis of frontotemporal lobar degeneration. Neurology 78(22), 1761–1768 (2012).
  • Likitjaroen Y, Meindl T, Friese U et al. Longitudinal changes of fractional anisotropy in Alzheimer’s disease patients treated with galantamine: a 12-month randomized, placebo-controlled, double-blinded study. Eur. Arch. Psychiatry Clin. Neurosci. 262(4), 341–350 (2012).
  • Jack CR Jr, Bernstein MA, Borowski BJ et al.; Alzheimer’s Disease Neuroimaging Initiative. Update on the magnetic resonance imaging core of the Alzheimer’s disease neuroimaging initiative. Alzheimers. Dement. 6(3), 212–220 (2010).
  • Jack CR Jr. Alzheimer disease: new concepts on its neurobiology and the clinical role imaging will play. Radiology 263(2), 344–361 (2012).
  • Yassa MA, Muftuler LT, Stark CE. Ultrahigh-resolution microstructural diffusion tensor imaging reveals perforant path degradation in aged humans in vivo. Proc. Natl Acad. Sci. USA 107(28), 12687–12691 (2010).
  • Greicius MD, Supekar K, Menon V, Dougherty RF. Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb. Cortex 19(1), 72–78 (2009).
  • Chételat G, Desgranges B, Landeau B et al. Direct voxel-based comparison between grey matter hypometabolism and atrophy in Alzheimer’s disease. Brain 131(Pt 1), 60–71 (2008).
  • Jacobs HI, Gronenschild EH, Evers EA et al. Visuospatial processing in early Alzheimer’s disease: a multimodal neuroimaging study. Cortex. doi:10.1016/j.cortex.2012.01.005 (2012) (Epub ahead of print).
  • Buckner RL, Andrews-Hanna JR, Schacter DL. The brain’s default network: anatomy, function, and relevance to disease. Ann. N. Y. Acad. Sci. 1124, 1–38 (2008).
  • Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc. Natl Acad. Sci. USA 98(2), 676–682 (2001).
  • Kantarci K, Lowe VJ, Boeve BF et al. Multimodality imaging characteristics of dementia with Lewy bodies. Neurobiol. Aging 33(9), 2091–2105 (2012).
  • Shaffer JL, Petrella JR, Sheldon FC et al.; Alzheimer’s Disease Neuroimaging Initiative. Predicting cognitive decline in subjects at risk for Alzheimer disease by using combined cerebrospinal fluid, MR imaging, and PET biomarkers. Radiology 266(2), 583–591 (2013).
  • Zhang D, Shen D. Predicting future clinical changes of MCI patients using longitudinal and multimodal biomarkers. PLoS ONE 7(3), e33182 (2012).
  • Kim J, Basak JM, Holtzman DM. The role of apolipoprotein E in Alzheimer’s disease. Neuron 63(3), 287–303 (2009).
  • Chiang GC, Zhan W, Schuff N, Weiner MW. White matter alterations in cognitively normal apoE e2 carriers: insight into Alzheimer resistance? AJNR. Am. J. Neuroradiol. 33(7), 1392–1397 (2012).
  • Forlenza OV, Diniz BS, Gattaz WF. Diagnosis and biomarkers of predementia in Alzheimer’s disease. BMC Med. 8, 89 (2010).
  • Hu WT, Holtzman DM, Fagan AM et al.; Alzheimer’s Disease Neuroimaging Initiative. Plasma multianalyte profiling in mild cognitive impairment and Alzheimer disease. Neurology 79(9), 897–905 (2012).
  • Mielke MM, Haughey NJ, Ratnam Bandaru VV et al. Plasma ceramides are altered in mild cognitive impairment and predict cognitive decline and hippocampal volume loss. Alzheimers. Dement. 6(5), 378–385 (2010).
  • Vemuri P, Wiste HJ, Weigand SD et al.; Alzheimer’s Disease Neuroimaging Initiative. MRI and CSF biomarkers in normal, MCI, and AD subjects: predicting future clinical change. Neurology 73(4), 294–301 (2009).
  • Thambisetty M, An Y, Kinsey A et al. Plasma clusterin concentration is associated with longitudinal brain atrophy in mild cognitive impairment. Neuroimage 59(1), 212–217 (2012).

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.