Skip to main content
SpringerLink
Log in

Vascular Cognitive Impairment

  • Chapter
  • First Online:
Book cover Handbook on the Neuropsychology of Aging and Dementia

Part of the book series: Clinical Handbooks in Neuropsychology ((CHNEURO))

Abstract

Cerebrovascular disease (CVD) is a universal aspect of the aging process. Nearly two thirds of individuals 70 years of age and older exhibit vascular lesions on structural brain scans. The neuropsychological phenotype of CVD can vary across individuals depending on the location and volume of the vascular damage, though most individuals exhibit impairment in executive function and psychomotor speed that ranges in severity from mild impairment to severe dementia. More than one third of individuals who survive a large vessel stroke exhibit dementia, with exponentially greater risk among those older than 65. In spite of the frequency and high individual, familial, and societal burden, progress in the field has been hampered by the application of inconsistent nomenclature, lack of objective and universal grading systems in radiology and neuropathology, and suboptimal sensitivity of clinical and research neuroimaging methods. These limitations underscore the value of clinical neuropsychology in the care and management of individuals with CVD. Through standardized methods, neuropsychological assessment provides the only means to evaluate functional brain integrity as it relates to performance. Further, neuropsychological assessment establishes a reference to determine the natural history of vascular cognitive impairment (VCI) over time and the potential benefit of therapeutic interventions. This chapter reviews the underlying biological features of VCI and related neuroimaging signatures. We review historic and contemporary perspectives on the neuropsychological phenotype of VCI, followed by recommendations to complete an evidence-based evaluation of neuropsychological status. We include a case example to illustrate the clinical application of the concepts reviewed in the chapter.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5). 4th ed. Washington, DC: American Psychiatric Pub; 2013.

    Book  Google Scholar 

  2. O’Brien JT, Erkinjuntti T, Reisberg B, et al. Vascular cognitive impairment. Lancet Neurol. 2003;2:89–98.

    Article  Google Scholar 

  3. Harmsen P, Rosengren A, Tsipogianni A, Wilhelmsen L. Risk factors for stroke in middle-aged men in Göteborg, Sweden. Stroke. 1990;21(2):223–9.

    Article  Google Scholar 

  4. Freudenberger, P., Schmidt, R., & Schmidt, H. Genetics of age-related white matter lesions from linkage to genome wide association studies. JNeurologic Sci. 2012;322(1), 82–86.

    Article  Google Scholar 

  5. Etherton MR, Wu O, Cougo P, et al. Integrity of normal-appearing white matter and functional outcomes after acute ischemic stroke. Neurology. 2017;88(18):1701–8.

    Article  Google Scholar 

  6. Madai VI, von Samson-Himmelstjerna FC, Bauer M, Stengl KL, Mutke MA, Tovar-Martinez E, Wuerfel J, Endres M, Niendorf T, Sobesky J. Ultrahigh-field MRI in human ischemic stroke–a 7 tesla study. PLoS One. 2012;7(5):e37631. Cardiology and machine learning

    Article  Google Scholar 

  7. Weng SF, Reps J, Kai J, Garibaldi JM, Qureshi N. Can machine-learning improve cardiovascular risk prediction using routine clinical data? PLoS One. 2017;12(4):e0174944. PMID: 28376093

    Article  Google Scholar 

  8. Convertino VA, Moulton SL, Grudic GZ, Rickards CA, Hinojosa-Laborde C, Gerhardt RT, Blackbourne LH, Ryan KL. Use of advanced machine-learning techniques for noninvasive monitoring of hemorrhage. J Trauma Acute Care Surg. 2011;71(1):S25–32.

    Article  Google Scholar 

  9. Looi JC, Sachdev PS. Vascular dementia as a frontal subcortical system dysfunction. Psychol Med. 2000;30(5):997–1003.

    Article  Google Scholar 

  10. Alberts MJ. Clinical presentation and diagnosis of cerebrovascular disease. In: Vascular medicine: a companion to Braunwald’s heart disease; 2013. p. 361–71.

    Chapter  Google Scholar 

  11. Garrett KD, Browndyke JN, Whelihan W, Paul RH, DiCarlo M, Moser DJ, et al. The neuropsychological profile of vascular cognitive impairment—no dementia: comparisons to patients at risk for cerebrovascular disease and vascular dementia. Arch Clin Neuropsychol. 2004;19:745–57.

    Article  Google Scholar 

  12. Jokinen H, Kalska H, Mantyla R, et al. Cognitive profile of subcortical ischaemic vascular disease. J Neurol Neurosurg Psychiatry. 2006;77:28–33.

    Article  Google Scholar 

  13. Sachdev PS, Brodaty H, Valenzuela MJ, Lorentz L, Looi JC, Wen W, Zagami AS. The neuropsychological profile of vascular cognitive impairment in stroke and TIA patients. Neurology. 2004;62(6):912–9.

    Article  Google Scholar 

  14. Zawacki TM, Grace J, Paul R, Moser DJ, Ott BR, Gordon N, Cohen RA. Behavioral problems as predictors of functional abilities of vascular dementia patients. J Neuropsychiatry Clin Neurosci. 2002;14(3):296–302.

    Article  Google Scholar 

  15. Kauhanen ML, Korpelainen JT, Hiltunen P, Määttä R, Mononen H, Brusin E, Sotaniemi KA, Myllylä VV. Aphasia, depression, and non-verbal cognitive impairment in ischaemic stroke. Cerebrovasc Dis. 2000;10(6):455–61.

    Article  Google Scholar 

  16. Paul R, Moser D, Cohen R, Browndyke J, Zawacki T, Gordon N. Dementia severity and pattern of cognitive performance in vascular dementia. Appl Neuropsychol. 2001;8(4):211–7.

    Article  Google Scholar 

  17. Sun JH, Tan L, Yu JT. Post-stroke cognitive impairment: epidemiology, mechanisms and management. Ann Transl Med. 2014;2(8):80. Williamson JB, Nyenhuis DL, Pedelty L, et al. Baseline differences between vascular cognitive impairment reverters and nonreverters. J Neurol Neurosurg Psychiatry 2008;79(11):1208–14.

    Google Scholar 

  18. Wentzel C, Rockwood K, MacKnight C, et al. Progression of impairment in patients with vascular cognitive impairment without dementia. Neurology. 2001;57(4):714–6.

    Article  Google Scholar 

  19. Lee J, Inoue M, Mlynash M, Mann SK, Cereda CW, Ke M, Albers GW, Olivot JM. MR perfusion lesions after TIA or minor stroke are associated with new infarction at 7 days. Neurology. 2017;88(24):2254–9.

    Article  Google Scholar 

  20. Cosentino SA, Jefferson AL, Carey ME, et al. The clinical diagnosis of vascular dementia: a comparison among four classification systems and a proposal for a new paradigm. Clin Neuropsychol. 2004;18(1):6–21.

    Article  Google Scholar 

  21. Lee JH, Kim SH, Kim GH, Seo SW, Park HK, Oh SJ, Kim JS, Cheong HK, Na DL. Identification of pure subcortical vascular dementia using 11C-Pittsburgh compound B. Neurology. 2011;77(1):18–25.

    Article  Google Scholar 

  22. Pachet A, Astner K, Brown L. Clinical utility of the mini-mental status examination when assessing decision-making capacity. J Geriatr Psychiatry Neurol. 2010;23(1):3–8.

    Article  Google Scholar 

  23. Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–9.

    Article  Google Scholar 

  24. Hachinski V, Iadecola C, Petersen RC, et al. National Institute of Neurological Disorders and Stroke-Canadian stroke network vascular cognitive impairment harmonization standards. Stroke. 2006;37(9):2220–41.

    Article  Google Scholar 

  25. Xu, Q., Cao, W. W., Mi, J. H., Yu, L., Lin, Y., & Li, Y. S. (2014). Brief screening for mild cognitive impairment in subcortical ischemic vascular disease: a comparison study of the Montreal cognitive assessment with the mini-mental state examination. European neurology, 71(3–4), 106–114.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Missouri Institute of Mental Health, St. Louis, MO, USA

    Robert Paul

  2. Department of Psychological Sciences, Division of Behavioral Neurosciences, 1 University Blvd, St. Louis, MO, USA

    Robert Paul

  3. Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, CA, USA

    Lauren Salminen

Authors
  1. Robert Paul
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lauren Salminen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Robert Paul .

Editor information

Editors and Affiliations

  1. Department of Neurology, Weill Cornell Medicine, New York, NY, USA

    Lisa D. Ravdin

  2. Department of Neurology, University of Miami, Miami, FL, USA

    Heather L. Katzen

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Paul, R., Salminen, L. (2019). Vascular Cognitive Impairment. In: Ravdin, L.D., Katzen, H.L. (eds) Handbook on the Neuropsychology of Aging and Dementia. Clinical Handbooks in Neuropsychology. Springer, Cham. https://doi.org/10.1007/978-3-319-93497-6_30

Download citation

Publish with us

Policies and ethics

Search

Navigation