Ferri CP, Prince M, Brayne C, Brodaty H, Fratiglioni L, Ganguli M, et al. Global prevalence of dementia: a Delphi consensus study. Lancet. 2005;366(9503):2112–7. doi:10.1016/S0140-6736(05)67889-0.
PubMed
PubMed Central
Google Scholar
Dementia: a public health priority. World Health Organization. 2012.
Google Scholar
Mattson MP. Pathways towards and away from Alzheimer’s disease. Nature. 2004;430(7000):631–9. doi:10.1038/nature02621.
CAS
PubMed
PubMed Central
Google Scholar
Tulving E. Episodic memory: from mind to brain. Annu Rev Psychol. 2002;53:1–25. doi:10.1146/annurev.psych.53.100901.135114.
PubMed
Google Scholar
Moorhouse P, Rockwood K. Vascular cognitive impairment: current concepts and clinical developments. Lancet Neurol. 2008;7(3):246–55. doi:10.1016/S1474-4422(08)70040-1.
PubMed
Google Scholar
Erkinjuntti T. Subcortical ischemic vascular disease and dementia. Int Psychogeriatr. 2003;15 Suppl 1:23–6. doi:10.1017/S1041610203008925.
PubMed
Google Scholar
Gorelick PB, Scuteri A, Black SE, Decarli C, Greenberg SM, Iadecola C, et al. Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the american heart association/american stroke association. Stroke. 2011;42(9):2672–713. doi:10.1161/STR.0b013e3182299496.
PubMed
PubMed Central
Google Scholar
Breteler MM, van Swieten JC, Bots ML, Grobbee DE, Claus JJ, van den Hout JH, et al. Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam Study. Neurology. 1994;44(7):1246–52.
CAS
PubMed
Google Scholar
Jellinger KA, Attems J. Neuropathological evaluation of mixed dementia. J Neurol Sci. 2007;257(1–2):80–7. doi:10.1016/j.jns.2007.01.045.
CAS
PubMed
Google Scholar
Kalaria RN. The role of cerebral ischemia in Alzheimer’s disease. Neurobiol Aging. 2000;21(2):321–30.
CAS
PubMed
Google Scholar
Rockwood K, Macknight C, Wentzel C, Black S, Bouchard R, Gauthier S, et al. The diagnosis of “mixed” dementia in the Consortium for the Investigation of Vascular Impairment of Cognition (CIVIC). Ann N Y Acad Sci. 2000;903:522–8.
CAS
PubMed
Google Scholar
Schneider JA, Arvanitakis Z, Bang W, Bennett DA. Mixed brain pathologies account for most dementia cases in community-dwelling older persons. Neurology. 2007;69(24):2197–204. doi:10.1212/01.wnl.0000271090.28148.24.
PubMed
Google Scholar
Zekry D, Hauw JJ, Gold G. Mixed dementia: epidemiology, diagnosis, and treatment. J Am Geriatr Soc. 2002;50(8):1431–8.
PubMed
Google Scholar
Wang BW, Lu E, Mackenzie IR, Assaly M, Jacova C, Lee PE, et al. Multiple pathologies are common in Alzheimer patients in clinical trials. Can J Neurol Sci. 2012;39(5):592–9.
CAS
PubMed
Google Scholar
Jellinger KA, Attems J. Prevalence of dementia disorders in the oldest-old: an autopsy study. Acta Neuropathol. 2010;119(4):421–33. doi:10.1007/s00401-010-0654-5.
PubMed
Google Scholar
Dubois B, Feldman HH, Jacova C, Cummings JL, Dekosky ST, Barberger-Gateau P, et al. Revising the definition of Alzheimer’s disease: a new lexicon. Lancet Neurol. 2010;9(11):1118–27. doi:10.1016/S1474-4422(10)70223-4.
PubMed
Google Scholar
Esiri MM, Nagy Z, Smith MZ, Barnetson L, Smith AD. Cerebrovascular disease and threshold for dementia in the early stages of Alzheimer’s disease. Lancet. 1999;354(9182):919–20. doi:10.1016/S0140-6736(99)02355-7.
CAS
PubMed
Google Scholar
Nagy Z, Esiri MM, Jobst KA, Morris JH, King EM, McDonald B, et al. The effects of additional pathology on the cognitive deficit in Alzheimer disease. J Neuropathol Exp Neurol. 1997;56(2):165–70.
CAS
PubMed
Google Scholar
Rosen WG, Mohs RC, Davis KL. A new rating scale for Alzheimer’s disease. Am J Psychiatry. 1984;141(11):1356–64.
CAS
PubMed
Google Scholar
Royall DR, Mahurin RK, Gray KF. Bedside assessment of executive cognitive impairment: the executive interview. J Am Geriatr Soc. 1992;40(12):1221–6.
CAS
PubMed
Google Scholar
Koski L. Validity and applications of the Montreal cognitive assessment for the assessment of vascular cognitive impairment. Cerebrovasc Dis. 2013;36(1):6–18. doi:10.1159/000352051.
PubMed
Google Scholar
O’Brien J, Lilienfeld S. Relevant clinical outcomes in probable vascular dementia and Alzheimer’s disease with cerebrovascular disease. J Neurol Sci. 2002;203–204:41–8.
PubMed
Google Scholar
Mohs RC, Kawas C, Carrillo MC. Optimal design of clinical trials for drugs designed to slow the course of Alzheimer’s disease. Alzheimers Dement. 2006;2(3):131–9. doi:10.1016/j.jalz.2006.04.003.
CAS
PubMed
Google Scholar
Hachinski V, Iadecola C, Petersen RC, Breteler MM, Nyenhuis DL, Black SE, et al. National Institute of Neurological Disorders and Stroke-Canadian Stroke Network vascular cognitive impairment harmonization standards. Stroke. 2006;37(9):2220–41. doi:10.1161/01.STR.0000237236.88823.47.
PubMed
Google Scholar
Liu-Ambrose T, Eng JJ, Boyd LA, Jacova C, Davis JC, Bryan S, et al. Promotion of the mind through exercise (PROMoTE): a proof-of-concept randomized controlled trial of aerobic exercise training in older adults with vascular cognitive impairment. BMC Neurol. 2010;10:14. doi:10.1186/1471-2377-10-14.
PubMed
PubMed Central
Google Scholar
Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–9. doi:10.1111/j.1532-5415.2005.53221.x.
PubMed
Google Scholar
Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98.
CAS
PubMed
Google Scholar
Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging. 1998;17(1):87–97. doi:10.1109/42.668698.
CAS
PubMed
Google Scholar
Smith SMB JM. SUSAN-a new approach to low level image processing. Int J Comput Vis. 1997;23:1.
Google Scholar
Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17(3):143–55. doi:10.1002/hbm.10062.
PubMed
Google Scholar
McAusland J, Tam R, Wong E, Riddehough A, Li D. Optimizing the Use of Radiologist Seed Points for Improved Multiple Sclerosis Lesion Segmentation. IEEE Trans Biomed Eng. 2010. doi:10.1109/TBME.2010.2055865.
PubMed
Google Scholar
Parzen E. On estimation of a probability density function and mode. Ann Math Stat. 1962;33:1065–76.
Google Scholar
Lam B, Middleton LE, Masellis M, Stuss DT, Harry RD, Kiss A, et al. Criterion and convergent validity of the Montreal cognitive assessment with screening and standardized neuropsychological testing. J Am Geriatr Soc. 2013;61(12):2181–5. doi:10.1111/jgs.12541.
PubMed
Google Scholar
Dong Y, Sharma VK, Chan BP, Venketasubramanian N, Teoh HL, Seet RC, et al. The Montreal Cognitive Assessment (MoCA) is superior to the Mini-Mental State Examination (MMSE) for the detection of vascular cognitive impairment after acute stroke. J Neurol Sci. 2010;299(1–2):15–8. doi:10.1016/j.jns.2010.08.051.
PubMed
Google Scholar
Kirk A. Target symptoms and outcome measures: cognition. Can J Neurol Sci. 2007;34 Suppl 1:S42–6.
PubMed
Google Scholar
Stokholm J, Vogel A, Gade A, Waldemar G. The executive interview as a screening test for executive dysfunction in patients with mild dementia. J Am Geriatr Soc. 2005;53(9):1577–81. doi:10.1111/j.1532-5415.2005.53470.x.
PubMed
Google Scholar
Royall DR, Rauch R, Roman GC, Cordes JA, Polk MJ. Frontal MRI findings associated with impairment on the Executive Interview (EXIT25). Exp Aging Res. 2001;27(4):293–308. doi:10.1080/03610730109342350.
CAS
PubMed
Google Scholar
Roman GC, Royall DR. Executive control function: a rational basis for the diagnosis of vascular dementia. Alzheimer Dis Assoc Disord. 1999;13 Suppl 3:S69–80.
PubMed
Google Scholar
Royall DR, Chiodo LK, Polk MJ. Executive dyscontrol in normal aging: normative data, factor structure, and clinical correlates. Curr Neurol Neurosci Rep. 2003;3(6):487–93.
PubMed
Google Scholar
Wechsler D. Wechsler adult intelligence scale. 4edth ed. New York: NCS Pearson; 2008.
Google Scholar
Trenerry M. Stroop neuropsychological screening test manual. Odessa, FL: Psychological Assessment Resources; 1989.
Google Scholar
Allen DN, Haderlie MM. Trail-making test. The Corsini Encyclopedia of Psychology: Wiley; 2010.
Google Scholar
Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab. 2007;27(9):1533–9. doi:10.1038/sj.jcbfm.9600493.
CAS
PubMed
Google Scholar
Logan J, Fowler JS, Volkow ND, Wang GJ, Ding YS, Alexoff DL. Distribution volume ratios without blood sampling from graphical analysis of PET data. J Cereb Blood Flow Metab. 1996;16(5):834–40. doi:10.1097/00004647-199609000-00008.
CAS
PubMed
Google Scholar
Logan J, Fowler JS, Volkow ND, Wolf AP, Dewey SL, Schlyer DJ, et al. Graphical analysis of reversible radioligand binding from time-activity measurements applied to [N-11C-methyl]-(−)-cocaine PET studies in human subjects. J Cereb Blood Flow Metab. 1990;10(5):740–7. doi:10.1038/jcbfm.1990.127.
CAS
PubMed
Google Scholar
Lopresti BJ, Klunk WE, Mathis CA, Hoge JA, Ziolko SK, Lu X, et al. Simplified quantification of Pittsburgh Compound B amyloid imaging PET studies: a comparative analysis. J Nucl Med. 2005;46(12):1959–72.
CAS
PubMed
Google Scholar
Price JC, Klunk WE, Lopresti BJ, Lu X, Hoge JA, Ziolko SK, et al. Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B. J Cereb Blood Flow Metab. 2005;25(11):1528–47. doi:10.1038/sj.jcbfm.9600146.
CAS
PubMed
Google Scholar
Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr. 1994;18(2):192–205.
CAS
PubMed
Google Scholar
Park JH, Seo SW, Kim C, Kim SH, Kim GH, Kim ST, et al. Effects of cerebrovascular disease and amyloid beta burden on cognition in subjects with subcortical vascular cognitive impairment. Neurobiol Aging. 2014;35(1):254–60. doi:10.1016/j.neurobiolaging.2013.06.026.
CAS
PubMed
Google Scholar
Aizenstein HJ, Nebes RD, Saxton JA, Price JC, Mathis CA, Tsopelas ND, et al. Frequent amyloid deposition without significant cognitive impairment among the elderly. Arch Neurol. 2008;65(11):1509–17. doi:10.1001/archneur.65.11.1509.
PubMed
PubMed Central
Google Scholar
Jagust WJ, Bandy D, Chen K, Foster NL, Landau SM, Mathis CA, et al. The Alzheimer’s Disease Neuroimaging Initiative positron emission tomography core. Alzheimers Dement. 2010;6(3):221–9. doi:10.1016/j.jalz.2010.03.003.
PubMed
PubMed Central
Google Scholar
Yaqub M, Tolboom N, Boellaard R, van Berckel BN, van Tilburg EW, Luurtsema G, et al. Simplified parametric methods for [11C] PIB studies. NeuroImage. 2008;42(1):76–86. doi:10.1016/j.neuroimage.2008.04.251.
PubMed
Google Scholar
Hsiung GY, Sadovnick AD, Feldman H. Apolipoprotein E epsilon4 genotype as a risk factor for cognitive decline and dementia: data from the Canadian Study of Health and Aging. CMAJ. 2004;171(8):863–7. doi:10.1503/cmaj.1031789.
PubMed
PubMed Central
Google Scholar
Doraiswamy PM, Sperling RA, Johnson K, Reiman EM, Wong TZ, Sabbagh MN, et al. Florbetapir F 18 amyloid PET and 36-month cognitive decline: a prospective multicenter study. Mol Psychiatry. 2014;19(9):1044–51. doi:10.1038/mp.2014.9.
CAS
PubMed
PubMed Central
Google Scholar
Resnick SM, Sojkova J, Zhou Y, An Y, Ye W, Holt DP, et al. Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C] PiB. Neurology. 2010;74(10):807–15. doi:10.1212/WNL.0b013e3181d3e3e9.
CAS
PubMed
PubMed Central
Google Scholar
Villemagne VL, Pike KE, Darby D, Maruff P, Savage G, Ng S, et al. Abeta deposits in older non-demented individuals with cognitive decline are indicative of preclinical Alzheimer’s disease. Neuropsychologia. 2008;46(6):1688–97. doi:10.1016/j.neuropsychologia.2008.02.008.
CAS
PubMed
Google Scholar
Forsberg A, Engler H, Almkvist O, Blomquist G, Hagman G, Wall A, et al. PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging. 2008;29(10):1456–65. doi:10.1016/j.neurobiolaging.2007.03.029.
CAS
PubMed
Google Scholar
Pike KE, Savage G, Villemagne VL, Ng S, Moss SA, Maruff P, et al. Beta-amyloid imaging and memory in non-demented individuals: evidence for preclinical Alzheimer’s disease. Brain. 2007;130(Pt 11):2837–44. doi:10.1093/brain/awm238.
PubMed
Google Scholar
Okello A, Koivunen J, Edison P, Archer HA, Turkheimer FE, Nagren K, et al. Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. Neurology. 2009;73(10):754–60. doi:10.1212/WNL.0b013e3181b23564.
CAS
PubMed
PubMed Central
Google Scholar
Wolk DA, Price JC, Saxton JA, Snitz BE, James JA, Lopez OL, et al. Amyloid imaging in mild cognitive impairment subtypes. Ann Neurol. 2009;65(5):557–68. doi:10.1002/ana.21598.
PubMed
PubMed Central
Google Scholar
Collette F, Van der Linden M, Salmon E. Executive dysfunction in Alzheimer’s disease. Cortex. 1999;35(1):57–72.
CAS
PubMed
Google Scholar
Sgaramella TM, Borgo F, Mondini S, Pasini M, Toso V, Semenza C. Executive deficits appearing in the initial stage of Alzheimer’s disease. Brain Cogn. 2001;46(1–2):264–8.
CAS
PubMed
Google Scholar
Gibbons LE, Carle AC, Mackin RS, Harvey D, Mukherjee S, Insel P, et al. A composite score for executive functioning, validated in Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants with baseline mild cognitive impairment. Brain Imaging Behav. 2012;6(4):517–27. doi:10.1007/s11682-012-9176-1.
PubMed
PubMed Central
Google Scholar
Lee MJ, Seo SW, Na DL, Kim C, Park JH, Kim GH, et al. Synergistic effects of ischemia and beta-amyloid burden on cognitive decline in patients with subcortical vascular mild cognitive impairment. JAME Psychiatry. 2014;71(4):412–22. doi:10.1001/jamapsychiatry.2013.4506.
Google Scholar
Nordlund A, Rolstad S, Klang O, Edman A, Hansen S, Wallin A. Two-year outcome of MCI subtypes and aetiologies in the Goteborg MCI study. J Neurol Neurosurg Psychiatry. 2010;81(5):541–6. doi:10.1136/jnnp.2008.171066.
PubMed
Google Scholar
Bennett DA, Schneider JA, Wilson RS, Bienias JL, Arnold SE. Neurofibrillary tangles mediate the association of amyloid load with clinical Alzheimer disease and level of cognitive function. Arch Neurol. 2004;61(3):378–84. doi:10.1001/archneur.61.3.378.
PubMed
Google Scholar
Carmichael O, Schwarz C, Drucker D, Fletcher E, Harvey D, Beckett L, et al. Longitudinal changes in white matter disease and cognition in the first year of the Alzheimer disease neuroimaging initiative. Arch Neurol. 2010;67(11):1370–8. doi:10.1001/archneurol.2010.284.
PubMed
PubMed Central
Google Scholar
Pasi M, Salvadori E, Poggesi A, Ciolli L, Del Bene A, Marini S, et al. White matter microstructural damage in small vessel disease is associated with Montreal Cognitive Assessment but not with mini mental state examination performances: Vascular Mild Cognitive Impairment Tuscany study. Stroke. 2015;46(1):262–4. doi:10.1161/STROKEAHA.114.007553.
PubMed
Google Scholar
Van Petten C, Plante E, Davidson PS, Kuo TY, Bajuscak L, Glisky EL. Memory and executive function in older adults: relationships with temporal and prefrontal gray matter volumes and white matter hyperintensities. Neuropsychologia. 2004;42(10):1313–35. doi:10.1016/j.neuropsychologia.2004.02.009.
PubMed
Google Scholar
Rolstad S, Berg AI, Eckerstrom C, Johansson B, Wallin A. Differential Impact of Neurofilament Light Subunit on Cognition and Functional Outcome in Memory Clinic Patients with and without Vascular Burden. J Alzheimers Dis. 2015;45(3):873–81. doi:10.3233/JAD-142694.
CAS
PubMed
Google Scholar
Lee JH, Kim SH, Kim GH, Seo SW, Park HK, Oh SJ, et al. Identification of pure subcortical vascular dementia using 11C-Pittsburgh compound B. Neurology. 2011;77(1):18–25. doi:10.1212/WNL.0b013e318221acee.
CAS
PubMed
Google Scholar