Volumetric MRI as a Diagnostic Tool in Alzheimer’s Disease

  • Eric Westman
  • Lena Cavalin
  • Lars-Olof WahlundEmail author
Part of the Methods in Pharmacology and Toxicology book series (MIPT)


Brain atrophy is one of the key features of Alzheimer’s disease (AD), and neuroimaging techniques, such as computer tomography (CT) and magnetic resonance imaging (MRI), have made it possible to study this pathological process in vivo. However, the use of clinical imaging in dementia evaluation is often suboptimal. Evidence supports the role of regional and global atrophy as well as white matter changes as markers of disease in dementia. There is an urgent need to apply this knowledge to optimize clinical imaging practice. In the following chapter we describe different methods to measure or estimate brain structures and white matter changes. Methods to judge the presence and distribution of cerebral microbleeds are also discussed. We describe both methods that are used in clinical practice today and methods that are still only applied in research or in clinical trials. The more advanced automated methods to estimate brain atrophy as well as other changes will hopefully be implemented in clinical practice in the future.

Key words

Magnetic resonance imaging Volumetry Medial temporal lobe atrophy Dementia Alzheimer’s disease Multivariate analyses 


  1. 1.
    Braak H, Braak E (1991) Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 82(4):239–259CrossRefPubMedGoogle Scholar
  2. 2.
    Jack CR Jr, Petersen RC, Xu Y et al (1998) Rate of medial temporal lobe atrophy in typical aging and Alzheimer’s disease. Neurology 51(4):993–999CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Jack CR Jr, Petersen RC, Xu YC et al (1997) Medial temporal atrophy on MRI in normal aging and very mild Alzheimer’s disease. Neurology 49(3):786–794CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    de Souza LC, Chupin M, Bertoux M et al (2013) Is hippocampal volume a good marker to differentiate Alzheimer’s disease from frontotemporal dementia? J Alzheimers Dis 36(1):57–66. doi: 10.3233/JAD-122293 PubMedGoogle Scholar
  5. 5.
    Laakso MP, Partanen K, Riekkinen P et al (1996) Hippocampal volumes in Alzheimer’s disease, Parkinson’s disease with and without dementia, and in vascular dementia: An MRI study. Neurology 46(3):678–681CrossRefPubMedGoogle Scholar
  6. 6.
    Scheltens P, Leys D, Barkhof F et al (1992) Atrophy of medial temporal lobes on MRI in “probable” Alzheimer’s disease and normal ageing: diagnostic value and neuropsychological correlates. J Neurol Neurosurg Psychiatry 55(10):967–972CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Koedam EL, Lehmann M, van der Flier WM et al (2011) Visual assessment of posterior atrophy development of a MRI rating scale. Eur Radiol 21(12):2618–2625. doi: 10.1007/s00330-011-2205-4 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Pasquier F, Leys D, Weerts JG et al (1996) Inter- and intraobserver reproducibility of cerebral atrophy assessment on MRI scans with hemispheric infarcts. Eur Neurol 36(5):268–272CrossRefPubMedGoogle Scholar
  9. 9.
    Westman E, Cavallin L, Muehlboeck JS et al (2011) Sensitivity and specificity of medial temporal lobe visual ratings and multivariate regional MRI classification in Alzheimer’s disease. PLoS ONE 6(7), e22506. doi: 10.1371/journal.pone.0022506, PONE-D-11-06805 [pii]CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Boche D, Zotova E, Weller RO et al (2008) Consequence of Abeta immunization on the vasculature of human Alzheimer’s disease brain. Brain 131(Pt 12):3299–3310. doi: 10.1093/brain/awn261 CrossRefPubMedGoogle Scholar
  11. 11.
    Orgogozo JM, Gilman S, Dartigues JF et al (2003) Subacute meningoencephalitis in a subset of patients with AD after Abeta42 immunization. Neurology 61(1):46–54CrossRefPubMedGoogle Scholar
  12. 12.
    Sperling RA, Jack CR Jr, Black SE et al (2011) Amyloid-related imaging abnormalities in amyloid-modifying therapeutic trials: recommendations from the Alzheimer’s Association Research Roundtable Workgroup. Alzheimers Dement 7(4):367–385. doi: 10.1016/j.jalz.2011.05.2351 CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Wahlund LO, Julin P, Johansson SE et al (2000) Visual rating and volumetry of the medial temporal lobe on magnetic resonance imaging in dementia: a comparative study. J Neurol Neurosurg Psychiatry 69(5):630–635CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Wahlund LO, Julin P, Lindqvist J et al (1999) Visual assessment of medical temporal lobe atrophy in demented and healthy control subjects: correlation with volumetry. Psychiatry Res 90(3):193–199CrossRefPubMedGoogle Scholar
  15. 15.
    Scheltens P, Launer LJ, Barkhof F et al (1995) Visual assessment of medial temporal lobe atrophy on magnetic resonance imaging: interobserver reliability. J Neurol 242(9):557–560CrossRefPubMedGoogle Scholar
  16. 16.
    Cavallin L, Bronge L, Zhang Y et al (2012) Comparison between visual assessment of MTA and hippocampal volumes in an elderly, non-demented population. Acta Radiol 53(5):573–579. doi: 10.1258/ar.2012.110664 CrossRefPubMedGoogle Scholar
  17. 17.
    Pereira JB, Cavallin L, Spulber G et al (2013) Influence of age, disease onset and ApoE4 on visual medial temporal lobe atrophy cut-offs. J Intern Med. doi: 10.1111/joim.12148 PubMedGoogle Scholar
  18. 18.
    Karas G, Scheltens P, Rombouts S et al (2007) Precuneus atrophy in early-onset alzheimer’s disease: a morphometric structural MRI study. Neuroradiology 49(12):967–976. doi: 10.1007/s00234-007-0269-2 CrossRefPubMedGoogle Scholar
  19. 19.
    Wahlund LO, Barkhof F, Fazekas F et al (2001) A new rating scale for age-related white matter changes applicable to MRI and CT. Stroke 32(6):1318–1322. doi: 10.1161/01.str.32.6.1318 CrossRefPubMedGoogle Scholar
  20. 20.
    Fazekas F, Chawluk JB, Alavi A et al (1987) MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. Am J Roentgenol 149(2):351–356. doi: 10.2214/ajr.149.2.351
  21. 21.
    Inzitari D, Pracucci G, Poggesi A et al. (2009) Changes in white matter as determinant of global functional decline in older independent outpatients: three year follow-up of LADIS (leukoaraiosis and disability) study cohort. BMJ 339:b2477. doi: 10.1136/bmj.b2477
  22. 22.
    Cordonnier C, Potter GM, Jackson CA et al (2009) Improving interrater agreement about brain microbleeds: development of the Brain Observer MicroBleed Scale (BOMBS). Stroke 40(1):94–99. doi: 10.1161/STROKEAHA.108.526996 CrossRefPubMedGoogle Scholar
  23. 23.
    Gregoire SM, Chaudhary UJ, Brown MM et al (2009) The microbleed anatomical rating scale (MARS): reliability of a tool to map brain microbleeds. Neurology 73(21):1759–1766. doi: 10.1212/WNL.0b013e3181c34a7d CrossRefPubMedGoogle Scholar
  24. 24.
    Hampel H, Bürger K, Teipel SJ et al (2008) Core candidate neurochemical and imaging biomarkers of Alzheimer’s disease. Alzheimers Dement 4(1):38–48CrossRefPubMedGoogle Scholar
  25. 25.
    Howard MA, Roberts N, Garcia-Finana M et al (2003) Volume estimation of prefrontal cortical subfields using MRI and stereology. Brain Res Brain Res Protoc 10(3):125–138CrossRefPubMedGoogle Scholar
  26. 26.
    Goncharova II, Dickerson BC, Stoub TR et al (2001) MRI of human entorhinal cortex: a reliable protocol for volumetric measurement. Neurobiol Aging 22(5):737–745CrossRefPubMedGoogle Scholar
  27. 27.
    Jack CR Jr, Theodore WH, Cook M et al (1995) MRI-based hippocampal volumetrics: data acquisition, normal ranges, and optimal protocol. Magn Reson Imaging 13(8):1057–1064CrossRefPubMedGoogle Scholar
  28. 28.
    Eritaia J, Wood SJ, Stuart GW et al (2000) An optimized method for estimating intracranial volume from magnetic resonance images. Magn Reson Med 44(6):973–977CrossRefPubMedGoogle Scholar
  29. 29.
    Teipel SJ, Pruessner JC, Faltraco F et al (2006) Comprehensive dissection of the medial temporal lobe in AD: measurement of hippocampus, amygdala, entorhinal, perirhinal and parahippocampal cortices using MRI. J Neurol 253(6):794–800. doi: 10.1007/s00415-006-0120-4 CrossRefPubMedGoogle Scholar
  30. 30.
    Giannakopoulos P, Kovari E, Gold G et al (2009) Pathological substrates of cognitive decline in Alzheimer’s disease. Front Neurol Neurosci 24:20–29. doi: 10.1159/000197881 CrossRefPubMedGoogle Scholar
  31. 31.
    Teipel SJ, Grothe M, Lista S et al (2013) Relevance of magnetic resonance imaging for early detection and diagnosis of Alzheimer disease. Med Clin N Am 97(3):399–424. doi: 10.1016/j.mcna.2012.12.013, http://dx.doi.orgCrossRefPubMedGoogle Scholar
  32. 32.
    Jack CR Jr, Petersen RC, Xu YC et al (1999) Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology 52(7):1397–1403CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Convit A, De Leon MJ, Tarshish C et al (1997) Specific hippocampal volume reductions in individuals at risk for Alzheimer’s disease. Neurobiol Aging 18(2):131–138CrossRefPubMedGoogle Scholar
  34. 34.
    Killiany RJ, Moss MB, Albert MS et al (1993) Temporal lobe regions on magnetic resonance imaging identify patients with early Alzheimer’s disease. Arch Neurol 50(9):949–954CrossRefPubMedGoogle Scholar
  35. 35.
    Frisoni GB, Jack CR (2011) Harmonization of magnetic resonance-based manual hippocampal segmentation: a mandatory step for wide clinical use. Alzheimers Dement 7(2):171–174. doi: 10.1016/j.jalz.2010.06.007 CrossRefPubMedGoogle Scholar
  36. 36.
    Hampel H, Lista S, Teipel SJ et al (2014) Perspective on future role of biological markers in clinical therapy trials of Alzheimer’s disease: a long-range point of view beyond 2020. Biochem Pharmacol 88(4):426–449. doi: 10.1016/j.bcp.2013.11.009 CrossRefPubMedGoogle Scholar
  37. 37.
    Jack CR, Slomkowski M, Gracon S et al (2003) MRI as a biomarker of disease progression in a therapeutic trial of milameline for AD. Neurology 60(2):253–260. doi: 10.1212/01.wnl.0000042480.86872.03 CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Wilkinson D, Fox NC, Barkhof F et al (2012) Memantine and brain atrophy in Alzheimer’s disease: a 1-year randomized controlled trial. J Alzheimers Dis 29(2):459–469. doi: 10.3233/JAD-2011-111616 PubMedGoogle Scholar
  39. 39.
    Fox NC, Black RS, Gilman S et al (2005) Effects of Aβ immunization (AN1792) on MRI measures of cerebral volume in Alzheimer disease. Neurology 64(9):1563–1572. doi: 10.1212/01.wnl.0000159743.08996.99 CrossRefPubMedGoogle Scholar
  40. 40.
    Ashburner J, Friston KJ (2000) Voxel-based morphometry—the methods. Neuroimage 11(6 Pt 1):805–821. doi: 10.1006/nimg.2000.0582 CrossRefPubMedGoogle Scholar
  41. 41.
    Desikan RS, Ségonne F, Fischl B et al (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31(3):968–980CrossRefPubMedGoogle Scholar
  42. 42.
    Fischl B, van der Kouwe A, Destrieux C et al (2004) Automatically parcellating the human cerebral cortex. Cereb Cortex 14(1):11–22CrossRefPubMedGoogle Scholar
  43. 43.
    Hanseeuw BJ, Van Leemput K, Kavec M et al (2011) Mild cognitive impairment: differential atrophy in the hippocampal subfields. Am J Neuroradiol 32(9):1658–1661. doi: 10.3174/ajnr.A2589
  44. 44.
    Lindberg O, Walterfang M, Looi JC et al (2012) Hippocampal shape analysis in Alzheimer’s disease and frontotemporal lobar degeneration subtypes. J Alzheimers Dis 30(2):355–365. doi: 10.3233/JAD-2012-112210 PubMedGoogle Scholar
  45. 45.
    Whitwell JL, Dickson DW, Murray ME et al (2012) Neuroimaging correlates of pathologically defined subtypes of Alzheimer’s disease: a case-control study. Lancet Neurol 11(10):868–877. doi: 10.1016/S1474-4422(12)70200-4 CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Damangir S, Manzouri A, Oppedal K et al (2012) Multispectral MRI segmentation of age related white matter changes using a cascade of support vector machines. J Neurol Sci 322(1-2):211–216. doi: 10.1016/j.jns.2012.07.064 CrossRefPubMedGoogle Scholar
  47. 47.
    Smith AD, Smith SM, de Jager CA et al (2010) Homocysteine-lowering by B vitamins slows the rate of accelerated brain atrophy in mild cognitive impairment: a randomized controlled trial. PLoS One 5(9), e12244. doi: 10.1371/journal.pone.0012244 CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Douaud G, Refsum H, de Jager CA et al (2013) Preventing Alzheimer’s disease-related gray matter atrophy by B-vitamin treatment. Proc Natl Acad Sci U S A 110(23):9523–9528. doi: 10.1073/pnas.1301816110 CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Cuingnet R, Gerardin E, Tessieras J et al (2011) Automatic classification of patients with Alzheimer’s disease from structural Magnetic Resonance Imaging (MRI): a comparison of ten methods using the ADNI database. Neuroimage 56(2):766–781. doi: 10.1016/j.neuroimage.2010.06.013, doi:S1053-8119(10)00857-8 [pii]
  50. 50.
    Davatzikos C, Bhatt P, Shaw LM et al. (2011) Prediction of MCI to AD conversion, via MRI, CSF biomarkers, and pattern classification. Neurobiol Aging. doi:S0197-4580(10)00237-X [pii], 10.1016/j.neurobiolaging.2010.05.023Google Scholar
  51. 51.
    Spulber G, Simmons A, Muehlboeck JS et al (2013) An MRI-based index to measure the severity of Alzheimer’s disease-like structural pattern in subjects with mild cognitive impairment. J Intern Med 273(4):396–409. doi: 10.1111/joim.12028 CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Westman E, Simmons A, Muehlboeck JS et al (2011) AddNeuroMed and ADNI: similar patterns of Alzheimer’s atrophy and automated MRI classification accuracy in Europe and North America. Neuroimage 58(3):818–828. doi: 10.1016/j.neuroimage.2011.06.065, doi:S1053-8119(11)00711-7 [pii]CrossRefPubMedGoogle Scholar
  53. 53.
    Davatzikos C, Fan Y, Wu X et al (2008) Detection of prodromal Alzheimer’s disease via pattern classification of magnetic resonance imaging. Neurobiol Aging 29(4):514–523. doi: 10.1016/j.neurobiolaging.2006.11.010, doi:S0197-4580(06)00429-5 [pii]CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Zhang D, Wang Y, Zhou L et al (2011) Multimodal classification of Alzheimer’s disease and mild cognitive impairment. Neuroimage 55(3):856–867CrossRefPubMedPubMedCentralGoogle Scholar
  55. 55.
    Westman E, Muehlboeck JS, Simmons A (2012) Combining MRI and CSF measures for classification of Alzheimer’s disease and prediction of mild cognitive impairment conversion. Neuroimage 62(1):229–238. doi: 10.1016/j.neuroimage.2012.04.056, doi:S1053-8119(12)00452-1 [pii]CrossRefPubMedGoogle Scholar
  56. 56.
    McEvoy LK, Fennema-Notestine C, Roddey JC et al. (2009) Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment. Radiology:2511080924. doi: 10.1148/radiol.2511080924
  57. 57.
    Falahati F, Westman E, Simmons A (2014) Multivariate data analysis and machine learning in Alzheimer’s disease with a focus on structural magnetic resonance imaging. J Alzheimers Dis 41(3):685–708. doi: 10.3233/JAD-131928 PubMedGoogle Scholar
  58. 58.
    Walhovd KB, Fjell AM, Brewer J et al (2010) Combining MR imaging, positron-emission tomography, and CSF biomarkers in the diagnosis and prognosis of Alzheimer disease. Am J Neuroradiol 31(2):347–354. doi: 10.3174/ajnr.A1809, doi:ajnr.A1809 [pii]
  59. 59.
    Mattila J, Koikkalainen J, Virkki A et al (2011) A disease state fingerprint for evaluation of Alzheimer’s disease. J Alzheimers Dis 27(1):163–176. doi: 10.3233/JAD-2011-110365 PubMedGoogle Scholar
  60. 60.
    Dubois B, Feldman HH, Jacova C et al (2007) Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDS-ADRDA criteria. Lancet Neurol 6(8):734–746CrossRefPubMedGoogle Scholar
  61. 61.
    McKhann GM, Knopman DS, Chertkow H et al (2011) 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. Alzheimers Dement 7(3):263–269. doi: 10.1016/j.jalz.2011.03.005, doi:S1552-5260(11)00101-4 [pii]CrossRefPubMedPubMedCentralGoogle Scholar
  62. 62.
    Zarow C, Vinters HV, Ellis WG et al (2005) Correlates of hippocampal neuron number in Alzheimer’s disease and ischemic vascular dementia. Ann Neurol 57(6):896–903. doi: 10.1002/ana.20503 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Eric Westman
    • 1
  • Lena Cavalin
    • 2
    • 3
  • Lars-Olof Wahlund
    • 1
    Email author
  1. 1.Department of Neurobiology, Care Sciences and SocietyKarolinska InstitutetStockholmSweden
  2. 2.Department of Clinical Science, Intervention and TechnologyKarolinska InstitutetStockholmSweden
  3. 3.Department of RadiologyKarolinska University HospitalStockholmSweden

Personalised recommendations