Skip to main content

Neuroimaging in Dementia

A Clinical Approach

  • Living reference work entry
  • First Online:
Clinical Neuroradiology

Abstract

Dementia is not a diagnosis or a specific disease entity but a syndrome that describes a wide range of symptoms leading to a decline in mental ability severe enough to interfere with daily life.

Neurodegenerative disorders including dementing disorders and movement disorders may present with overlapping clinical symptoms. Likewise, the underlying molecular and cellular pathology may be overlapping. Consequently, dementia syndromes and movement disorders may be considered as a spectrum of diseases, and symptoms may vary over time. Moreover, there is no direct link between clinical symptoms and imaging findings: the same degree of brain atrophy or metabolic abnormality may be associated to a variable degree of cognitive impairment, or from the other perspective, the same degree of cognitive impairment may be associated with variable level of brain atrophy or metabolic abnormality. Finally, it is not uncommon to have coexisting pathology, for example, Alzheimer type neurodegeneration and a vascular contribution.

In the first part, we review basic clinical presentations of dementia syndromes. In the second part, we review the radiological techniques and typical clinical neuroradiology findings of the various types of dementia, including Alzheimer dementia (hippocampal atrophy, hypometabolism/hypoperfusion in posterior cingulate and bilateral parietal areas), vascular dementia (small and large vessel disease), fronto-temporal lobar degeneration (fronto-temporal/peri-insular atrophy and hypometabolism/hypoperfusion), and dementia with Lewy Bodies (reduced dopamine uptake in striatum, abnormality of the nigrosome1). Additionally, we review unusual clinical presentations of dementia, including young-onset dementia and rapidly progressive dementia. Finally, we briefly discuss the overlapping clinical presentation and underlying pathology between dementia and movement disorders.

This publication is endorsed by: European Society of Neuroradiology (www.esnr.org)

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

Access this chapter

Institutional subscriptions

Similar content being viewed by others

Abbreviations

AD:

Alzheimer disease

ASL:

Arterial spin labeling

bvFTD:

Behavioral variant fronto-temporal dementia

CAA:

Cerebral amyloid angiopathy

CADASIL:

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy

CBD:

Corticobasal disease

CBS:

Corticobasal syndrome

CJD:

Creutzfeldt-Jakob disease

CMB:

Cerebral microbleeds

CTE:

Chronic traumatic encephalopathy

DAT:

Dopamine transporter

DLB:

Dementia with Lewy bodies

FDG:

Fluoro-deoxy-glucose

FTD:

Frontotemporal dementia

FTLD:

Fronto-temporal lobar degeneration

LVD:

Large vessel disease

MCI:

Mild cognitive impairment

MSA:

Multisystem atrophy

MSA-c:

MSA cerebellar type

MSA-p:

MSA Parkinsonian type

PCA:

Posterior cortical atrophy

PCC:

Posterior cingulate cortex

PD:

Parkinson disease

PNFA:

Progressive nonfluent aphasia

PPA:

Primary progressive aphasia

PSP:

Progressive supranuclear palsy

SD:

Semantic dementia

SVD:

Small vessel disease

VaD:

Vascular dementia

WMH:

White matter hyperintensities

References

  • Benamer TS, Patterson J, Grosset DG, et al. Accurate differentiation of parkinsonism and essential tremor using visual assessment of [123I]-FP-CIT SPECT imaging: the [123I]-FP-CIT study group. Mov Disord. 2000;15:503–10.

    Article  CAS  Google Scholar 

  • Haller S, Vernooij MW, Kuijer JPA, et al. Cerebral microbleeds: imaging and clinical significance. Radiology. 2018;287:11–28.

    Article  Google Scholar 

  • Lindberg O, Ostberg P, Zandbelt BB, et al. Cortical morphometric subclassification of frontotemporal lobar degeneration. AJNR Am J Neuroradiol. 2009;30:1233–9.

    Article  CAS  Google Scholar 

  • Paterson RW, Takada LT, Geschwind MD. Diagnosis and treatment of rapidly progressive dementias. Neurol Clin Pract. 2012;2:187–200.

    Article  Google Scholar 

  • Petersen RC. Alzheimer’s disease: progress in prediction. Lancet Neurol. 2010;9:4–5.

    Article  Google Scholar 

  • Trojanowski JQ, Vandeerstichele H, Korecka M, et al. Update on the biomarker core of the Alzheimer’s disease Neuroimaging Initiative subjects. Alzheimers Dement. 2010;6:230–8.

    Article  CAS  Google Scholar 

  • Winblad B, Amouyel P, Andrieu S, et al. Defeating Alzheimer’s disease and other dementias: a priority for European science and society. Lancet Neurol. 2016;15:455–532.

    Article  Google Scholar 

Further Reading

  • Cash DM, Bocchetta M, Thomas DL, et al. Patterns of gray matter atrophy in genetic frontotemporal dementia: results from the GENFI study. Neurobiol Aging. 2018;62:191–6.

    Article  Google Scholar 

  • Haller S, Barkhof F. Interaction of vascular damage and Alzheimer dementia: focal damage and disconnection. Radiology. 2017;282:311–3.

    Article  Google Scholar 

  • Haller S, Garibotto V, Kövari E, et al. Neuroimaging of dementia in 2013: what radiologists need to know. Eur Radiol. 2013a;23:3393–404.

    Article  Google Scholar 

  • Haller S, Kövari E, Herrmann FR, et al. Do brain T2/FLAIR white matter hyperintensities correspond to myelin loss in normal aging? A radiologic-neuropathologic correlation study. Acta Neuropathol Commun. 2013b;1:14.

    Article  Google Scholar 

  • Haller S, Fällmar D, Larsson EM. Susceptibility weighted imaging in dementia with Lewy bodies: will it resolve the blind spot of MRI. Neuroradiology. 2016;58:217–8.

    Article  Google Scholar 

  • http://www.radiologyassistant.nl/en/p43dbf6d16f98d/dementia-role-of-mri.html

  • http://www.springer.com/de/book/9783642008177

  • Jack CRJ, Knopman DS, Jagust WJ, et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol. 2010;9:119–28.

    Article  CAS  Google Scholar 

  • Jack CR, Knopman DS, Weigand SD, et al. An operational approach to National Institute on Aging-Alzheimer’s Association criteria for preclinical Alzheimer disease. Ann Neurol. 2012;71:765–75.

    Article  Google Scholar 

  • Josephs KA, Whitwell JL, Knopman DS, et al. Two distinct subtypes of right temporal variant frontotemporal dementia. Neurology. 2009;73:1443–50.

    Article  CAS  Google Scholar 

  • Kamminga J, Kumfor F, Burrell JR, Piguet O, Hodges JR, Irish M. Differentiating between right-lateralised semantic dementia and behavioural-variant frontotemporal dementia: an examination of clinical characteristics and emotion processing. J Neurol Neurosurg Psychiatry. 2015;86:1082–8.

    Article  Google Scholar 

  • Pereira JB, Cavallin L, Spulber G, et al. Influence of age, disease onset and ApoE4 on visual medial temporal lobe atrophy cut-offs. J Intern Med. 2014;275:317–30.

    Article  CAS  Google Scholar 

  • Roman GC, Tatemichi TK, Erkinjuntti T, et al. Vascular dementia: diagnostic criteria for research studies. Report of the NINDS-AIREN International Workshop. Neurology. 1993;43:250–60.

    Article  CAS  Google Scholar 

  • Rohrer JD. Structural brain imaging in frontotemporal dementia. Biochim Biophys Acta. 2012;1822:325–32.

    Article  CAS  Google Scholar 

  • Rossor MN, Fox NC, Mummery CJ, Schott JM, Warren JD. The diagnosis of young-onset dementia. Lancet Neurol. 2010;9:793–806.

    Article  Google Scholar 

  • Schwarz ST, Afzal M, Morgan PS, Bajaj N, Gowland PA, Auer DP. The ‘swallow tail’ appearance of the healthy nigrosome – a new accurate test of Parkinson’s disease: a case-control and retrospective cross-sectional MRI study at 3T. PLoS One. 2014;9:e93814.

    Article  Google Scholar 

  • van Straaten EC, Scheltens P, Knol DL, et al. Operational definitions for the NINDS-AIREN criteria for vascular dementia: an interobserver study. Stroke. 2003;34:1907–12.

    Article  Google Scholar 

  • Whitwell JL, Dickson DW, Murray ME, et al. Neuroimaging correlates of pathologically defined subtypes of Alzheimer’s disease: a case-control study. Lancet Neurol. 2012;11:868–77.

    Article  Google Scholar 

  • Ylikoski A, Erkinjuntti T, Raininko R, Sarna S, Sulkava R, Tilvis R. White matter hyperintensities on MRI in the neurologically nondiseased elderly. Analysis of cohorts of consecutive subjects aged 55 to 85 years living at home. Stroke. 1995;26:1171–7.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sven Haller .

Editor information

Editors and Affiliations

Section Editor information

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Haller, S., Barkhof, F. (2018). Neuroimaging in Dementia. In: Barkhof, F., Jager, R., Thurnher, M., Rovira Cañellas, A. (eds) Clinical Neuroradiology. Springer, Cham. https://doi.org/10.1007/978-3-319-61423-6_64-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-61423-6_64-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61423-6

  • Online ISBN: 978-3-319-61423-6

  • eBook Packages: Springer Reference MedicineReference Module Medicine

Publish with us

Policies and ethics