Skip to main content
SpringerLink
Log in

Welche bildgebenden Verfahren sind in der Demenzdiagnostik sinnvoll?

MRT, PET und SPECT

  • Zertifizierte Fortbildung
  • Published:
DNP - Der Neurologe und Psychiater Aims and scope

Zusammenfassung

Morphologische, funktionelle und molekulare bildgebende Verfahren erfahren einen wachsenden Stellenwert in der Demenzdiagnostik. Vor allem in der differenzialdiagnostischen Einordnung der zugrunde liegenden Erkrankung und ihrer Abgrenzung gegenüber potenziell reversiblen somatischenoder neuropsychiatrischen Ursachen einer demenziellen Entwicklung finden sie klinische Anwendung.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Literatur

  1. Bickel H. Epidemiologie und Gesundheitsökonomie. In: Wallesch CW, Förstl H (Hrsg) Demenzen. Referenzreihe Neurologie. Thieme Verlag, Stuttgart. 2005;S 1–15.

    Google Scholar 

  2. Prince M, Bryce R, Albanese E, Wimo A, Ribeiro W, Ferri CP. The global prevalence of dementia: a systematic review and metaanalysis. Alzheimer’s & dementia: the journal of the Alzheimer’s Association. 2013;9(1):63–75 e2.

    Article  Google Scholar 

  3. Buschert VC, Giegling I, Teipel SJ, Jolk S, Hampel H, Rujescu D, et al. Long-term observation of a multicomponent cognitive intervention in mild cognitive impairment. J Clin Psychiatry. 2012;73(12):e1492–1498.

    Article  Google Scholar 

  4. WHO, Dilling H, Mombour W, et al.: Internationale Klassifikation psychischer Störungen. ICD-10 Kapitel V (F), Klinisch-diagnostische Leitlinien. 6. Aufl. Bern, Huber 2008.

    Google Scholar 

  5. Hardy J. The amyloid hypothesis for Alzheimer’s disease: a critical reappraisal. J Neurochem. 2009;110(4):1129–1134.

    Article  PubMed  CAS  Google Scholar 

  6. Jack CR, Jr. Alzheimer disease: new concepts on its neurobiology and the clinical role imaging will play. Radiology. 2012;263(2):344–361.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Jonsson T, Atwal JK, Steinberg S, Snaedal J, Jonsson PV, Bjornsson S, et al. A mutation in APP protects against Alzheimer’s disease and age-related cognitive decline. Nature. 2012;488(7409):96–99.

    Article  PubMed  CAS  Google Scholar 

  8. Jack CR, Jr., Knopman DS, Jagus WJ, Shaw LM, Aisen PS, Weiner MW, et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol. 2010;9(1):119–128.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  9. Jack CR, Jr., Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12(2):207–216.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  10. Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, 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. 2011;7(3):280–92.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):270–279.

    Article  PubMed  PubMed Central  Google Scholar 

  12. 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):2220–2241.

    Article  PubMed  Google Scholar 

  13. Gold G, Kovari E, Herrmann FR, Canuto A, Hof PR, Michel JP, et al. Cognitive consequences of thalamic, basal ganglia, and deep white matter lacunes in brain aging and dementia. Stroke. 2005;36(6):1184–1188.

    Article  PubMed  Google Scholar 

  14. Brown WR, Moody DM, Thore CR, Challa VR, Anstrom JA. Vascular dementia in leukoaraiosis may be a consequence of capillary loss not only in the lesions, but in normal-appearing white matter and cortex as well. J Neurol Sci. 2007;257(1-2):62–66.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Zipser BD, Johanson CE, Gonzalez L, Berzin TM, Tavares R, Hulette CM, et al. Microvascular injury and blood-brain barrier leakage in Alzheimer’s disease. Neurobiol Aging. 2007;28(7):977–986.

    Article  PubMed  CAS  Google Scholar 

  16. Neary D, Snowden JS, Gustafson L, Passant U, Stuss D, Black S, et al. Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology. 1998;51(6):1546–1554.

    Article  PubMed  CAS  Google Scholar 

  17. McKeith IG, Dickson DW, Lowe J, Emre M, O’Brien JT, Feldman H, et al. Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology. 2005;65(12):1863–1872.

    Article  PubMed  CAS  Google Scholar 

  18. Gifford DR, Holloway RG, Vickrey BG. Systematic review of clinical prediction rules for neuroimaging in the evaluation of dementia. Archives of internal medicine. 2000;160(18):2855–2862.

    Article  PubMed  CAS  Google Scholar 

  19. Dickerson BC, Goncharova I, Sullivan MP, Forchetti C, Wilson RS, Bennett DA, et al. MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer’s disease. Neurobiol Aging. 2001;22(5):747–754.

    Article  PubMed  CAS  Google Scholar 

  20. Devanand DP, Liu X, Tabert MH, Pradhaban G, Cuasay K, Bell K, et al. Combining early markers strongly predicts conversion from mild cognitive impairment to Alzheimer’s disease. Biol Psychiatry. 2008;64(10):871–879.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Teipel SJ, Bokde AL, Born C, Meindl T, Reiser M, Möller HJ, et al. Morphological substrate of face matching in healthy ageing and mild cognitive impairment: a combined MRI-fMRI study. Brain. 2007;130(Pt 7):1745–1758.

    Article  PubMed  Google Scholar 

  22. Bokde AL, Karmann M, Teipel SJ, Born C, Lieb M, Reiser MF, et al. Decreased activation along the dorsal visual pathway after a 3-month treatment with galantamine in mild Alzheimer disease: a functional magnetic resonance imaging study. J Clin Psychopharmacol. 2009;29(2):147–156.

    Article  PubMed  CAS  Google Scholar 

  23. Meindl T, Teipel S, Elmouden R, Mueller S, Koch W, Dietrich O, et al. Test-retest reproducibility of the default-mode network in healthy individuals. Human brain mapping.31(2):237-246.

  24. Koch W, Teipel S, Mueller S, Benninghoff J, Wagner M, Bokde AL, et al. Diagnostic power of default mode network resting state fMRI in the detection of Alzheimer’s disease. Neurobiology of aging. 2012;33(3):466–478.

    Article  PubMed  Google Scholar 

  25. Mosconi L, Tsui WH, Herholz K, Pupi A, Drzezga A, Lucignani G, et al. Multicenter standardized 18F-FDG PET diagnosis of mild cognitive impairment, Alzheimer’s disease, and other dementias. Journal of nuclear medicine: official publication, Society of Nuclear Medicine. 2008;49(3):390–398.

    Article  Google Scholar 

  26. Lehmann M, Rohrer JD, Clarkson MJ, Ridgway GR, Scahill RI, Modat M, et al. Reduced cortical thickness in the posterior cingulate gyrus is characteristic of both typical and atypical Alzheimer’s disease. J Alzheimers Dis. 2010;20(2):587–598.

    PubMed  Google Scholar 

  27. Minoshima S, Giordani B, Berent S, Frey KA, Foster NL, Kuhl DE. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann Neurol. 1997;42(1):85–94.

    Article  PubMed  CAS  Google Scholar 

  28. Bohnen NI, Djang DS, Herholz K, Anzai Y, Minoshima S. Effectiveness and safety of 18F-FDG PET in the evaluation of dementia: a review of the recent literature. J Nucl Med. 2012;53(1):59–71.

    Article  PubMed  CAS  Google Scholar 

  29. Foster NL, Heidebrink JL, Clark CM, Jagust WJ, Arnold SE, Barbas NR, et al. FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer’s disease. Brain. 2007;130(Pt 10):2616–2635.

    Article  PubMed  Google Scholar 

  30. Minoshima S, Frey KA, Koeppe RA, Foster NL, Kuhl DE. A diagnostic approach in Alzheimer’s disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. Journal of nuclear medicine: official publication, Society of Nuclear Medicine. 1995;36(7):1238–1248.

    CAS  Google Scholar 

  31. Quigley H, Colloby SJ, O’Brien JT. PET imaging of brain amyloid in dementia: a review. Int J Geriatr Psychiatry. 2011;26(10):991–999.

    Article  PubMed  Google Scholar 

  32. McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR, Jr., Kawas CH, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & dementia: the journal of the Alzheimer’s Association. 2011;7(3):263–269.

    Article  Google Scholar 

  33. Pimlott SL, Ebmeier KP. SPECT imaging in dementia. Br J Radiol. 2007;80 Spec No 2:S153–159.

    Article  Google Scholar 

  34. Risacher SL, Saykin AJ, West JD, Shen L, Firpi HA, McDonald BC. Baseline MRI predictors of conversion from MCI to probable AD in the ADNI cohort. Curr Alzheimer Res. 2009;6(4):347–361.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  35. Jack CR, Jr., Petersen RC, Xu YC, O’Brien PC, Smith GE, Ivnik RJ, et al. Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology. 1999;52(7):1397–1403.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Barnes J, Bartlett JW, van de Pol LA, Loy CT, Scahill RI, Frost C, et al. A meta-analysis of hippocampal atrophy rates in Alzheimer’s disease. Neurobiol Aging. 2009;30(11):1711–1723.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Braak H, Braak E, Bohl J. Staging of Alzheimer-related cortical destruction. Eur Neurol. 1993;33(6):403–408.

    Article  PubMed  CAS  Google Scholar 

  38. Scheltens P, Leys D, Barkhof F, Huglo D, Weinstein HC, Vermersch P, et al. Atrophy of medial temporal lobes on MRI in „probable“ Alzheimer’s disease and normal ageing: diagnostic value and neuropsychological correlates. J Neurol Neurosurg Psychiatry. 1992;55(10):967–972.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  39. Duara R, Loewenstein DA, Potter E, Appel J, Greig MT, Urs R, et al. Medial temporal lobe atrophy on MRI scans and the diagnosis of Alzheimer disease. Neurology. 2008;71(24):1986–1992.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  40. Burton EJ, Barber R, Mukaetova-Ladinska EB, Robson J, Perry RH, Jaros E, et al. Medial temporal lobe atrophy on MRI differentiates Alzheimer’s disease from dementia with Lewy bodies and vascular cognitive impairment: a prospective study with pathological verification of diagnosis. Brain. 2009;132(Pt 1):195–203.

    Article  PubMed  CAS  Google Scholar 

  41. Jack CR, Jr., Bernstein MA, Borowski BJ, Gunter JL, Fox NC, Thompson PM, et al. Update on the magnetic resonance imaging core of the Alzheimer’s disease neuroimaging initiative. Alzheimers Dement. 2010;6(3):212–220.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Green RC, et al. The Alzheimer’s Disease Neuroimaging Initiative: a review of papers published since its inception. Alzheimers Dement. 2013;9(5):e111–194.

    Article  Google Scholar 

  43. Ellis RJ, Olichney JM, Thal LJ, Mirra SS, Morris JC, Beekly D, et al. Cerebral amyloid angiopathy in the brains of patients with Alzheimer’s disease: the CERAD experience, Part XV. Neurology. 1996;46(6):1592–1596.

    Article  PubMed  CAS  Google Scholar 

  44. Herholz K, Nordberg A, Salmon E, Perani D, Kessler J, Mielke R, et al. Impairment of neocortical metabolism predicts progression in Alzheimer’s disease. Dement Geriatr Cogn Disord. 1999;10(6):494–504.

    Article  PubMed  CAS  Google Scholar 

  45. Bloudek LM, Spackman DE, Blankenburg M, Sullivan SD. Review and meta-analysis of biomarkers and diagnostic imaging in Alzheimer’s disease. J Alzheimers Dis. 2011;26(4):627–645.

    PubMed  CAS  Google Scholar 

  46. 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. 9. England: Copyright (c) 2010 Elsevier Ltd. All rights reserved.; 2010. p. 1118–1127.

    Article  PubMed  Google Scholar 

  47. Yeo JM, Lim X, Khan Z, Pal S. Systematic review of the diagnostic utility of SPECT imaging in dementia. Eur Arch Psychiatry Clin Neurosci. 2013;263(7):539–552.

    Article  PubMed  Google Scholar 

  48. Rabinovici GD, Jagust WJ. Amyloid imaging in aging and dementia: testing the amyloid hypothesis in vivo. Behav Neurol. 2009;21(1):117–128.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  49. Cairns NJ, Ikonomovic MD, Benzinger T, Storandt M, Fagan AM, Shah AR, et al. Absence of Pittsburgh compound B detection of cerebral amyloid beta in a patient with clinical, cognitive, and cerebrospinal fluid markers of Alzheimer disease: a case report. Arch Neurol. 2009;66(12):1557–1562.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Petersen RC, Doody R, Kurz A, Mohs RC, Morris JC, Rabins PV, et al. Current concepts in mild cognitive impairment. Arch Neurol. 2001;58(12):1985–1992.

    Article  PubMed  CAS  Google Scholar 

  51. Valkanova V, Ebmeier KP. Neuroimaging in dementia. Maturitas. 2014.

    Google Scholar 

  52. Heiss WD, Zimmermann-Meinzingen S. PET imaging in the differential diagnosis of vascular dementia. J Neurol Sci. 2012;322(1-2):268–273.

    Article  PubMed  Google Scholar 

  53. Rosen HJ, Gorno-Tempini ML, Goldman WP, Perry RJ, Schuff N, Weiner M, et al. Patterns of brain atrophy in frontotemporal dementia and semantic dementia. Neurology. 2002;58(2):198–208.

    Article  PubMed  CAS  Google Scholar 

  54. Boccardi M, Laakso MP, Bresciani L, Galluzzi S, Geroldi C, Beltramello A, et al. The MRI pattern of frontal and temporal brain atrophy in fronto-temporal dementia. Neurobiol Aging. 2003;24(1):95–103.

    Article  PubMed  Google Scholar 

  55. Frisoni GB. Structural imaging in the clinical diagnosis of Alzheimer’s disease: problems and tools. J Neurol Neurosurg Psychiatry. 2001;70(6):711–718.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  56. Lojkowska W, Ryglewicz D, Jedrzejczak T, Sienkiewicz-Jarosz H, Minc S, Jakubowska T, et al. SPECT as a diagnostic test in the investigation of dementia. J Neurol Sci. 2002;203–204:215-9.

    Google Scholar 

  57. Dougall NJ, Bruggink S, Ebmeier KP. Systematic review of the diagnostic accuracy of 99mTc-HMPAO-SPECT in dementia. Am J Geriatr Psychiatry. 2004;12(6):554–570.

    Article  PubMed  Google Scholar 

  58. McMurtray AM, Chen AK, Shapira JS, Chow TW, Mishkin F, Miller BL, et al. Variations in regional SPECT hypoperfusion and clinical features in frontotemporal dementia. Neurology. 2006;66(4):517–522.

    Article  PubMed  CAS  Google Scholar 

  59. Gorno-Tempini ML, Dronkers NF, Rankin KP, Ogar JM, Phengrasamy L, Rosen HJ, et al. Cognition and anatomy in three variants of primary progressive aphasia. Ann Neurol. 2004;55(3):335–346.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Nestor PJ, Graham NL, Fryer TD, Williams GB, Patterson K, Hodges JR. Progressive non-fluent aphasia is associated with hypometabolism centred on the left anterior insula. Brain. 2003;126(Pt 11):2406–2418.

    Article  PubMed  Google Scholar 

  61. Borroni B, Grassi M, Agosti C, Paghera B, Alberici A, Di Luca M, et al. Latent profile analysis in frontotemporal lobar degeneration and related disorders: clinical presentation and SPECT functional correlates. BMC Neurol. 2007;7:9.

    Google Scholar 

  62. Rabinovici GD, Jagust WJ, Furst AJ, Ogar JM, Racine CA, Mormino EC, et al. Abeta amyloid and glucose metabolism in three variants of primary progressive aphasia. Ann Neurol. 2008;64(4):388–401.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Diehl-Schmid J, Grimmer T, Drzezga A, Bornschein S, Perneczky R, Forstl H, et al. Longitudinal changes of cerebral glucose metabolism in semantic dementia. Dement Geriatr Cogn Disord. 2006;22(4):346–351.

    Article  PubMed  CAS  Google Scholar 

  64. Whitwell JL, Weigand SD, Shiung MM, Boeve BF, Ferman TJ, Smith GE, et al. Focal atrophy in dementia with Lewy bodies on MRI: a distinct pattern from Alzheimer’s disease. Brain. 2007;130(Pt 3):708–719.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Vemuri P, Simon G, Kantarci K, Whitwell JL, Senjem ML, Przybelski SA, et al. Antemortem differential diagnosis of dementia pathology using structural MRI: Differential-STAND. Neuroimage. 2011;55(2):522–531.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Kantarci K, Ferman TJ, Boeve BF, Weigand SD, Przybelski S, Vemuri P, et al. Focal atrophy on MRI and neuropathologic classification of dementia with Lewy bodies. Neurology. 2012;79(6):553–560.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Walker Z, Jaros E, Walker RW, Lee L, Costa DC, Livingston G, et al. Dementia with Lewy bodies: a comparison of clinical diagnosis, FP-CIT single photon emission computed tomography imaging and autopsy. Journal of neurology, neurosurgery, and psychiatry. 2007;78(11):1176–1181.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Papathanasiou ND, Boutsiadis A, Dickson J, Bomanji JB. Diagnostic accuracy of (1)(2)(3)I-FP-CIT (DaTSCAN) in dementia with Lewy bodies: a meta-analysis of published studies. Parkinsonism Relat Disord. 2012;18(3):225–229.

    Article  PubMed  Google Scholar 

  69. Shattuck DW, Joshi AA, Pantazis D, Kan E, Dutton RA, Sowell ER, et al. Semi-automated method for delineation of landmarks on models of the cerebral cortex. Journal of neuroscience methods. 2009;178(2):385–392.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Ashburner J, Friston KJ. Unified segmentation. NeuroImage. 2005;26(3):839–851.

    Article  PubMed  Google Scholar 

  71. Dyrba M, Ewers M, Wegrzyn M, Kilimann I, Plant C, Oswald A, et al. Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data. PloS one. 2013;8(5):e64925.

    Article  Google Scholar 

  72. Chien DT, Bahri S, Szardenings AK, Walsh JC, Mu F, Su MY, et al. Early clinical PET imaging results with the novel PHF-tau radioligand [F-18]-T807. Journal of Alzheimer’s disease: JAD. 2013;34(2):457–468.

    PubMed  CAS  Google Scholar 

  73. Chien DT, Szardenings AK, Bahri S, Walsh JC, Mu F, Xia C, et al. Early clinical PET imaging results with the novel PHF-tau radioligand [F18]-T808. Journal of Alzheimer’s disease: JAD. 2014;38(1):171–184.

    PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Klinik und Poliklinik für Nuklearmedizin Klinikdirektor Prof. Dr. med. B. J. Krause, Universitätsmedizin Rostock, Gertrudenplatz 1, 18057, Rostock, Deutschland

    Monique Sakretz (Ärztin)

  2. Klinik und Poliklinik für Nuklearmedizin, Universitätsmedizin Rostock, Rostock, Deutschland

    Jens Kurth

  3. Zentrum für Nervenheilkunde, Klinik und Poliklinik für Psychosomatische Medizin, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) Standort, Universitätsmedizin Rostock, Rostock/Greifswald, Deutschland

    Stefan Teipel

  4. Klinik und Poliklinik für Nuklearmedizin, Universitätsmedizin Rostock, Rostock, Deutschland

    Bernd Joachim Krause

Authors
  1. Monique Sakretz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jens Kurth
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Stefan Teipel
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bernd Joachim Krause
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Monique Sakretz.

Additional information

Interessenkonflikt

Die Autoren erklären, dass sie sich bei der Erstellung des Beitrags von keinen wirtschaftlichen Interessen leiten ließen. Professor Teipel erklärt die Teilnahme an einer Phase-III-Studie als Studienzentrum, Lilly. Professor Krause erklärt Studienzusammenarbeit und den Bezug von Forschungsgeldern von TauRx Therapeutics Ltd. sowie die Studienzusammenarbeit mit GE. Der Verlag erklärt, dass die inhaltliche Qualität des Beitrags von zwei unabhängigen Gutachtern geprüft wurde. Werbung in dieser Zeitschriftenausgabe hat keinen Bezug zur CME-Fortbildung. Der Verlag garantiert, dass die CME-Fortbildung sowie die CME-Fragen frei sind von werblichen Aussagen und keinerlei Produktempfehlungen enthalten. Dies gilt insbesondere für Präparate, die zur Therapie der dargestellten Krankheitsbilder geeignet sind.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sakretz, M., Kurth, J., Teipel, S. et al. Welche bildgebenden Verfahren sind in der Demenzdiagnostik sinnvoll?. DNP 15, 38–49 (2014). https://doi.org/10.1007/s15202-014-0811-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s15202-014-0811-0

Search

Navigation