Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

The clinical use of structural MRI in Alzheimer disease

Abstract

Structural imaging based on magnetic resonance is an integral part of the clinical assessment of patients with suspected Alzheimer dementia. Prospective data on the natural history of change in structural markers from preclinical to overt stages of Alzheimer disease are radically changing how the disease is conceptualized, and will influence its future diagnosis and treatment. Atrophy of medial temporal structures is now considered to be a valid diagnostic marker at the mild cognitive impairment stage. Structural imaging is also included in diagnostic criteria for the most prevalent non-Alzheimer dementias, reflecting its value in differential diagnosis. In addition, rates of whole-brain and hippocampal atrophy are sensitive markers of neurodegeneration, and are increasingly used as outcome measures in trials of potentially disease-modifying therapies. Large multicenter studies are currently investigating the value of other imaging and nonimaging markers as adjuncts to clinical assessment in diagnosis and monitoring of progression. The utility of structural imaging and other markers will be increased by standardization of acquisition and analysis methods, and by development of robust algorithms for automated assessment.

Key Points

  • Brain atrophy detected by high-resolution MRI is correlated with both tau deposition and neuropsychological deficits, and is a valid marker of Alzheimer disease (AD) and its progression

  • The degree of atrophy of medial temporal structures such as the hippocampus is a diagnostic marker for AD at the mild cognitive impairment stage

  • Structural imaging markers are included in diagnostic criteria for non-AD dementias, such as vascular dementia, frontotemporal degeneration, dementia with Lewy bodies, and Creutzfeldt–Jakob disease, and can aid differential diagnosis

  • Whole-brain and hippocampal atrophy rates are sensitive markers of progression of neurodegeneration, and are increasingly used as surrogate outcomes in trials of potentially disease-modifying drugs

  • In the near future, imaging and cerebrospinal fluid markers of amyloid deposition and glucose metabolism could be integrated with automated assessment of structural markers for optimal diagnosis and monitoring

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Natural progression of cognitive and biological markers of Alzheimer disease: a theoretical model.
Figure 2: Progressive enrichment of a mild cognitive impairment cohort with future converters to Alzheimer dementia by screening for low hippocampal volume.
Figure 3: Effect of severe WMLs on the progression of cognitive deterioration.
Figure 4: Cortical thinning in patients with mild cognitive impairment.

Similar content being viewed by others

References

  1. Braak, H. & Braak, E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol. 82, 239–259 (1991).

    CAS  PubMed  Google Scholar 

  2. Delacourte, A. et al. The biochemical pathway of neurofibrillary degeneration in aging and Alzheimer's disease. Neurology 52, 1158–1165 (1999).

    CAS  PubMed  Google Scholar 

  3. McKhann, G. et al. Clinical diagnosis of Alzheimer's disease: report of the NINCDS–ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology 34, 939–944 (1984).

    CAS  PubMed  Google Scholar 

  4. Bosscher, L. & Scheltens, P. in Evidence-Based Dementia Practice (eds Qizilbash, N. et al.) 154–162 (Blackwell, Oxford, 2002).

    Google Scholar 

  5. Frisoni, G. B. et al. Neuroimaging tools to rate regional atrophy, subcortical cerebrovascular disease, and regional cerebral blood flow and metabolism: consensus paper of the EADC. J. Neurol. Neurosurg. Psychiatry 74, 1371–1381 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Ramani, A., Jensen, J. H. & Helpern, J. A. Quantitative MR imaging in Alzheimer disease. Radiology 241, 26–44 (2006).

    PubMed  Google Scholar 

  7. Whitwell, J. L. et al. MRI correlates of neurofibrillary tangle pathology at autopsy: a voxel-based morphometry study. Neurology 71, 743–749 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Vemuri, P. et al. MRI and CSF biomarkers in normal, MCI, and AD subjects: predicting future clinical change. Neurology 73, 294–301 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Thompson, P. M. et al. Mapping hippocampal and ventricular change in Alzheimer disease. Neuroimage 22, 1754–1766 (2004).

    PubMed  Google Scholar 

  10. Vemuri, P. et al. Antemortem MRI based structural abnormality index (STAND)-scores correlated with postmortem Braak neurofibrillary tangle stage. NeuroImage 4, 559–567 (2008).

    Google Scholar 

  11. Thompson, P. M. et al. Dynamics of gray matter loss in Alzheimer's disease. J. Neurosci. 23, 994–1005 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Scahill, R. I., Schott, J. M., Stevens, J. M., Rossor, M. N. & Fox, N. C. Mapping the evolution of regional atrophy in Alzheimer's disease: unbiased analysis of fluid-registered serial MRI. Proc. Natl Acad. Sci. USA 99, 4703–4707 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Frisoni, G. B. et al. The pilot European Alzheimer's Disease Neuroimaging Initiative of the European Alzheimer's Disease Consortium. Alzheimers Dement. 4, 255–264 (2008).

    PubMed  PubMed Central  Google Scholar 

  14. McDonald, C. R. et al. Regional rates of neocortical atrophy from normal aging to early Alzheimer disease. Neurology 73, 457–465 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Fox, N. C., Scahill, R. I., Crum, W. R. & Rossor, M. N. Correlation between rates of brain atrophy and cognitive decline in AD. Neurology 52, 1687–1689 (1999).

    CAS  PubMed  Google Scholar 

  16. Josephs, K. A. et al. β-amyloid burden is not associated with rates of brain atrophy. Ann. Neurol. 63, 204–212 (2008).

    PubMed  PubMed Central  Google Scholar 

  17. Schott, J. M. et al. Neuropsychological correlates of whole brain atrophy in Alzheimer's disease. Neuropsychologia 46, 1732–1737 (2008).

    CAS  PubMed  Google Scholar 

  18. Sluimer, J. D. et al. Whole-brain atrophy rate and CSF biomarker levels in MCI and AD: a longitudinal study. Neurobiol. Aging doi: 10.1016/j.neurobiolaging.2008.06.016.

    CAS  PubMed  Google Scholar 

  19. Sluimer, J. D. et al. Whole-brain atrophy rate and cognitive decline: longitudinal MR study of memory clinic patients. Radiology 248, 590–598 (2008).

    PubMed  Google Scholar 

  20. Cardenas, V. A. et al. Brain atrophy associated with baseline and longitudinal measures of cognition. Neurobiol. Aging doi: 10.1016/j.neurobiolaging.2009.04.011.

    CAS  PubMed  Google Scholar 

  21. Jack, C. R. Jr et al. Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD. Neurology 62, 591–600 (2004).

    PubMed  Google Scholar 

  22. Morra, J. H. et al. Automated 3D mapping of hippocampal atrophy and its clinical correlates in 400 subjects with Alzheimer's disease, mild cognitive impairment, and elderly controls. Hum. Brain Mapp. 30, 2766–2788 (2009).

    PubMed  PubMed Central  Google Scholar 

  23. Ridha, B. H. et al. Volumetric MRI and cognitive measures in Alzheimer disease: comparison of markers of progression. J. Neurol. 255, 567–574 (2008).

    PubMed  Google Scholar 

  24. Hua, X. et al. Optimizing power to track brain degeneration in Alzheimer's disease and mild cognitive impairment with tensor-based morphometry: an ADNI study of 515 subjects. NeuroImage 48, 668–681 (2009).

    PubMed  Google Scholar 

  25. Ho, A. et al. Comparing 3 Tesla and 1.5 Tesla MRI for tracking Alzheimer's disease progression with tensor-based morphometry. Hum. Brain Mapp. (in press).

  26. Jack, C. R. Jr et al. MRI as a biomarker of disease progression in a therapeutic trial of milameline for AD. Neurology 60, 253–260 (2003).

    PubMed  Google Scholar 

  27. Jack, C. R. Jr et al. Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: implications for sequence of pathological events in Alzheimer's disease. Brain 132, 1355–1365 (2009).

    PubMed  PubMed Central  Google Scholar 

  28. Pike, K. E. et al. β-amyloid imaging and memory in non-demented individuals: evidence for preclinical Alzheimer's disease. Brain 130, 2837–2844 (2007).

    PubMed  Google Scholar 

  29. Minoshima, S. et al. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease. Ann. Neurol. 42, 85–94 (1997).

    CAS  PubMed  Google Scholar 

  30. Engler, H. et al. Two-year follow-up of amyloid deposition in patients with Alzheimer's disease. Brain 129, 2856–2866 (2006).

    PubMed  Google Scholar 

  31. Ridha, B. H. et al. Tracking atrophy progression in familial Alzheimer's disease: a serial MRI study. Lancet Neurol. 5, 828–834 (2006).

    PubMed  Google Scholar 

  32. Fox, N. C. et al. Imaging of onset and progression of Alzheimer's disease with voxel-compression mapping of serial magnetic resonance images. Lancet 358, 201–205 (2001).

    CAS  PubMed  Google Scholar 

  33. Jack, C. R. et al. Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurol. 9, 119–128 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Adalsteinsson, E., Sullivan, E. V., Kleinhans, N., Spielman, D. M. & Pfefferbaum, A. Longitudinal decline of the neuronal marker N-acetyl aspartate in Alzheimer's disease. Lancet 355, 1696–1697 (2000).

    CAS  PubMed  Google Scholar 

  35. Kantarci, K. et al. DWI predicts future progression to Alzheimer's disease in amnestic mild cognitive impairment. Neurology 64, 902–904 (2005).

    CAS  PubMed  Google Scholar 

  36. Taoka, T. et al. Diffusion anisotropy and diffusivity of white matter tracts within the temporal stem in Alzheimer disease: evaluation of the “tract of interest” by diffusion tensor tractography. AJNR Am. J. Neuroradiol. 27, 1040–1045 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Ridha, B. H. et al. Magnetization transfer ratio in Alzheimer disease: comparison with volumetric measurements. Am. J. Neuroradiol. 28, 965–970 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. van der Flier, W. M. et al. Medial temporal lobe atrophy and white matter hyperintensities are associated with mild cognitive deficits in non-disabled elderly people: the LADIS study. J. Neurol. Neurosurg. Psychiatry 76, 1497–1500 (2005).

    CAS  Google Scholar 

  39. Johnson, N. A. et al. Pattern of cerebral hypoperfusion in Alzheimer disease and mild cognitive impairment measured with arterial spin-labeling MR imaging: initial experience. Radiology 234, 851–859 (2005).

    PubMed  Google Scholar 

  40. Alsop, D. C. & Press, D. Z. Activation and baseline changes in functional MRI studies of Alzheimer disease. Neurology 69, 1645–1646 (2007).

    PubMed  Google Scholar 

  41. Buckner, R. L. et al. Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory. J. Neurosci. 25, 7709–7717 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Sperling, R. A. et al. Amyloid deposition is associated with impaired default network function in older persons without dementia. Neuron 63, 178–188 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Dubois, B. et al. Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria. Lancet Neurol. 6, 734–746 (2007).

    PubMed  Google Scholar 

  44. Modrego, P. J. Predictors of conversion to dementia of probable Alzheimer type in patients with mild cognitive impairment. Curr. Alzheimer Res. 3, 161–170 (2006).

    CAS  PubMed  Google Scholar 

  45. Scheltens, 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 55, 967–972 (1992).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Korf, E. S., Wahlund, L. O., Visser, P. J. & Scheltens, P. Medial temporal lobe atrophy on MRI predicts dementia in patients with mild cognitive impairment. Neurology 63, 94–100 (2004).

    PubMed  Google Scholar 

  47. DeCarli, C. et al. Alzheimer's Disease Cooperative Study Group. Qualitative estimates of medial temporal atrophy as a predictor of progression from mild cognitive impairment to dementia. Arch. Neurol. 64, 108–115 (2007).

    PubMed  Google Scholar 

  48. Duara, R. et al. Medial temporal lobe atrophy on MRI scans and the diagnosis of Alzheimer disease. Neurology 71, 1986–1992 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Burton, E. J. 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 132, 195–203 (2009).

    CAS  PubMed  Google Scholar 

  50. Bobinski, M. et al. The histological validation of post mortem magnetic resonance imaging-determined hippocampal volume in Alzheimer's disease. Neuroscience 95, 721–725 (2000).

    CAS  PubMed  Google Scholar 

  51. Gosche, K. M., Mortimer, J. A., Smith, C. D., Markesbery, W. R. & Snowdon, D. A. Hippocampal volume as an index of Alzheimer neuropathology: findings from the Nun Study. Neurology 58, 1476–1482 (2002).

    CAS  PubMed  Google Scholar 

  52. Jack, C. R. Jr et al. Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia. Neurology 58, 750–757 (2002).

    PubMed  Google Scholar 

  53. Shi, F., Liu, B., Zhou, Y., Yu, C. & Jiang, T. Hippocampal volume and asymmetry in mild cognitive impairment and Alzheimer's disease: meta-analyses of MRI studies. Hippocampus 19, 1055–1064 (2009).

    PubMed  Google Scholar 

  54. Barnes, J. et al. Automatic calculation of hippocampal atrophy rates using a hippocampal template and the boundary shift integral. Neurobiol. Aging 28, 1657–1663 (2007).

    CAS  PubMed  Google Scholar 

  55. Yuan, Y., Gu, Z. X. & Wei, W. S. Fluorodeoxyglucose-positron-emission tomography, single-photon emission tomography, and structural MR imaging for prediction of rapid conversion to Alzheimer disease in patients with mild cognitive impairment: a meta-analysis. Am. J. Neuroradiol. 30, 404–410 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Visser, P. J., Scheltens, P. & Verhey, F. R. Do MCI criteria in drug trials accurately identify subjects with predementia Alzheimer's disease? J. Neurol. Neurosurg. Psychiatry 76, 1348–1354 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Hampel, H. & Broich, K. Enrichment of MCI and early Alzheimer's disease treatment trials using neurochemical and imaging candidate biomarkers. J. Nutr. Health Aging 13, 373–375 (2009).

    CAS  PubMed  Google Scholar 

  58. van de Pol, L. A. et al. Hippocampal atrophy on MRI in frontotemporal lobar degeneration and Alzheimer's disease. J. Neurol. Neurosurg. Psychiatry 77, 439–442 (2006).

    CAS  PubMed  Google Scholar 

  59. Likeman, M. et al. Visual assessment of atrophy on magnetic resonance imaging in the diagnosis of pathologically confirmed young-onset dementias. Arch. Neurol. 62, 1410–1415 (2005).

    PubMed  Google Scholar 

  60. Bouwman, F. H. et al. CSF biomarkers and medial temporal lobe atrophy predict dementia in mild cognitive impairment. Neurobiol. Aging 28, 1070–1074 (2007).

    CAS  PubMed  Google Scholar 

  61. Klöppel, S. et al. Automatic classification of MR scans in Alzheimer's disease. Brain 131, 681–689 (2008).

    PubMed  Google Scholar 

  62. Vemuri, P. et al. Alzheimer's disease diagnosis in individual subjects using structural MR images: validation studies. Neuroimage 39, 1186–1197 (2008).

    PubMed  Google Scholar 

  63. Mueller, S. G. & Weiner, M. W. Selective effect of age, Apo e4, and Alzheimer's disease on hippocampal subfields. Hippocampus 19, 558–564 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Teipel, S. J. et al. Measurement of basal forebrain atrophy in Alzheimer's disease using MRI. Brain 128, 2626–2644 (2005).

    PubMed  Google Scholar 

  65. Karas, G. et al. Amnestic mild cognitive impairment: structural MR imaging findings predictive of conversion to Alzheimer disease. Am. J. Neuroradiol. 29, 944–949 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Scheltens, P., Fox, N., Barkhof, F. & De Carli, C. Structural magnetic resonance imaging in the practical assessment of dementia: beyond exclusion. Lancet Neurol. 1, 13–21 (2002).

    PubMed  Google Scholar 

  67. Geroldi, C. et al. The added value of neuropsychologic tests and structural imaging for the etiologic diagnosis of dementia in Italian expert centers. Alzheimer Dis. Assoc. Disord. 22, 309–320 (2008).

    PubMed  Google Scholar 

  68. Román, G. C. et al. Vascular dementia: diagnostic criteria for research studies. Report of the NINDS–AIREN International Workshop. Neurology 43, 250–260 (1993).

    PubMed  Google Scholar 

  69. Neary, D., Snowden, J. & Mann, D. Frontotemporal dementia. Lancet Neurol. 4, 771–780 (2005).

    PubMed  Google Scholar 

  70. Pereira, J. M. et al. Atrophy patterns in histologic vs clinical groupings of frontotemporal lobar degeneration. Neurology 72, 1653–1660 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Rohrer, J. D. et al. Patterns of cortical thinning in the language variants of frontotemporal lobar degeneration. Neurology 72, 1562–1569 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. McKeith, I. G. et al. Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology 65, 1863–1872 (2005).

    CAS  PubMed  Google Scholar 

  73. Barber, R., Ballard, C., McKeith, I. G., Gholkar, A. & O'Brien, J. T. MRI volumetric study of dementia with Lewy bodies: a comparison with AD and vascular dementia. Neurology 54, 1304–1309 (2000).

    CAS  PubMed  Google Scholar 

  74. McKeith, I. et al. Sensitivity and specificity of dopamine transporter imaging with 123I-FP-CIT SPECT in dementia with Lewy bodies: a phase III, multicentre study. Lancet Neurol. 6, 305–313 (2007).

    PubMed  Google Scholar 

  75. Gilman, S. et al. Second consensus statement on the diagnosis of multiple system atrophy. Neurology 71, 670–676 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Schrag, A. et al. Differentiation of atypical parkinsonian syndromes with routine MRI. Neurology 54, 697–702 (2000).

    CAS  PubMed  Google Scholar 

  77. Watanabe, H. et al. Progression and prognosis in multiple system atrophy: an analysis of 230 Japanese patients. Brain 125, 1070–1083 (2002).

    PubMed  Google Scholar 

  78. Paviour, D. C., Price, S. L., Jahanshahi, M., Lees, A. J. & Fox, N. C. Regional brain volumes distinguish PSP, MSA-P, and PD: MRI-based clinico-radiological correlations. Mov. Disord. 21, 989–996 (2006).

    PubMed  Google Scholar 

  79. Collie, D. A. et al. MRI of Creutzfeldt–Jakob disease: imaging features and recommended MRI protocol. Clin. Radiol. 56, 726–739 (2001).

    CAS  PubMed  Google Scholar 

  80. Tschampa, H. J. et al. MRI in the diagnosis of sporadic Creutzfeldt–Jakob disease: a study on inter-observer agreement. Brain 128, 2026–2033 (2005).

    PubMed  Google Scholar 

  81. Macfarlane, R. G., Wroe, S. J., Collinge, J., Yousry, T. A. & Jäger, H. R. Neuroimaging findings in human prion disease. J. Neurol. Neurosurg. Psychiatry 78, 664–670 (2007).

    CAS  PubMed  Google Scholar 

  82. Zeidler, M. et al. The pulvinar sign on magnetic resonance imaging in variant Creutzfeldt–Jakob disease. Lancet 355, 1412–1418 (2000).

    CAS  PubMed  Google Scholar 

  83. DeCarli, C. et al. Cerebrovascular and brain morphologic correlates of mild cognitive impairment in the National Heart, Lung, and Blood Institute Twin Study. Arch. Neurol. 58, 643–647 (2001).

    CAS  PubMed  Google Scholar 

  84. Black, S. E., Patterson, C. & Feightner, J. Preventing dementia. Can. J. Neurol. Sci. 28, S56–S66 (2001).

    PubMed  Google Scholar 

  85. de Groot, J. C. et al. Cerebral white matter lesions and cognitive function: the Rotterdam Scan Study. Ann. Neurol. 47, 145–151 (2000).

    CAS  PubMed  Google Scholar 

  86. Schmidt, R., Petrovic, K., Ropele, S., Enzinger, C. & Fazekas, F. Progression of leukoaraiosis and cognition. Stroke 38, 2619–2625 (2007).

    PubMed  Google Scholar 

  87. Frisoni, G. B., Galluzzi, S., Pantoni, L. & Filippi, M. The effect of white matter lesions on cognition in the elderly—small but detectable. Nat. Clin. Pract. Neurol. 3, 620–627 (2007).

    PubMed  Google Scholar 

  88. Schmidt, R. et al. White matter lesion progression, brain atrophy, and cognitive decline: the Austrian stroke prevention study. Ann. Neurol. 58, 610–616 (2005).

    PubMed  Google Scholar 

  89. Vermeer, S. E. et al. Silent brain infarcts and the risk of dementia and cognitive decline. N. Engl. J. Med. 348, 1215–1222 (2003).

    PubMed  Google Scholar 

  90. Snowdon, D. A. et al. Brain infarction and the clinical expression of Alzheimer disease. The Nun Study. JAMA 277, 813–817 (1997).

    CAS  PubMed  Google Scholar 

  91. Cordonnier, C. et al. Prevalence and severity of microbleeds in a memory clinic setting. Neurology 66, 1356–1360 (2006).

    CAS  PubMed  Google Scholar 

  92. Henneman, W. J. et al. MRI biomarkers of vascular damage and atrophy predicting mortality in a memory clinic population. Stroke 40, 492–498 (2009).

    PubMed  Google Scholar 

  93. Goos, J. D. et al. Patients with Alzheimer disease with multiple microbleeds: relation with cerebrospinal fluid biomarkers and cognition. Stroke 40, 3455–3460 (2009).

    PubMed  Google Scholar 

  94. Fleming, T. R. Surrogate endpoints and FDA's accelerated approval process. Health Aff. (Millwood) 24, 67–78 (2005).

    Google Scholar 

  95. Prentice, R. L. Surrogate endpoints in clinical trials: definition and operational criteria. Stat. Med. 8, 431–440 (1989).

    CAS  Google Scholar 

  96. Fox, N. C., Cousens, S., Scahill, R., Harvey, R. J. & Rossor, M. N. Using serial registered brain magnetic resonance imaging to measure disease progression in Alzheimer disease: power calculations and estimates of sample size to detect treatment effects. Arch. Neurol. 57, 339–344 (2000).

    CAS  PubMed  Google Scholar 

  97. Evans, M. C. et al. Volume changes in Alzheimer's disease and mild cognitive impairment: cognitive associations. Eur. Radiol. doi: 10.1007/s00330-009-1581–1585.

  98. Gauthier, S. et al. Effect of tramiprosate in patients with mild-to-moderate Alzheimer's disease: exploratory analyses of the MRI sub-group of the Alphase study. J. Nutr. Health Aging 13, 550–557 (2009).

    CAS  PubMed  Google Scholar 

  99. Nestor, S. M. et al. Ventricular enlargement as a possible measure of Alzheimer's disease progression validated using the Alzheimer's disease neuroimaging initiative database. Brain 131, 2443–2454 (2008).

    PubMed  PubMed Central  Google Scholar 

  100. Ridha, B. H. et al. Tracking atrophy progression in familial Alzheimer's disease: a serial MRI study. Lancet Neurol. 5, 828–834 (2006).

    PubMed  Google Scholar 

  101. Chételat, G. et al. Using voxel-based morphometry to map the structural changes associated with rapid conversion in MCI: a longitudinal MRI study. Neuroimage 27, 934–946 (2005).

    PubMed  Google Scholar 

  102. Driscoll, I. et al. Longitudinal pattern of regional brain volume change differentiates normal aging from MCI. Neurology 72, 1906–1913 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  103. Hampel, H. et al. Correlation of cerebrospinal fluid levels of tau protein phosphorylated at threonine 231 with rates of hippocampal atrophy in Alzheimer disease. Arch. Neurol. 62, 770–773 (2005).

    PubMed  Google Scholar 

  104. Geuze, E., Vermetten, E. & Bremner, J. D. MR-based in vivo hippocampal volumetrics: 1. Review of methodologies currently employed. Mol. Psychiatry 10, 147–159 (2005).

    CAS  PubMed  Google Scholar 

  105. Schott, J. M. et al. Measuring atrophy in Alzheimer disease: a serial MRI study over 6 and 12 months. Neurology 65, 119–124 (2005).

    CAS  PubMed  Google Scholar 

  106. Fox, N. C. & Kennedy, J. Structural imaging markers for therapeutic trials in Alzheimer's disease. J. Nutr. Health Aging 13, 350–352 (2009).

    CAS  PubMed  Google Scholar 

  107. Schuff, N. et al. MRI of hippocampal volume loss in early Alzheimer's disease in relation to ApoE genotype and biomarkers. Brain 132, 1067–1077 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. van de Pol, L. A. et al. Improved reliability of hippocampal atrophy rate measurement in mild cognitive impairment using fluid registration. Neuroimage 34, 1036–1041 (2007).

    CAS  PubMed  Google Scholar 

  109. Colliot, O. et al. Discrimination between Alzheimer disease, mild cognitive impairment, and normal aging by using automated segmentation of the hippocampus. Radiology 248, 194–201 (2008).

    PubMed  Google Scholar 

  110. Morra, J. H. et al. Validation of a fully automated 3D hippocampal segmentation method using subjects with Alzheimer's disease mild cognitive impairment, and elderly controls. Neuroimage 43, 59–68 (2008).

    PubMed  Google Scholar 

  111. Khan, A. R., Wang, L. & Beg, M. F. FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping. Neuroimage 41, 735–746 (2008).

    PubMed  Google Scholar 

  112. Fox, N. C. et al. Effects of Aβ immunization (AN1792) on MRI measures of cerebral volume in Alzheimer disease. Neurology 64, 1563–1572 (2005).

    CAS  PubMed  Google Scholar 

  113. Frisoni, G. B. & Delacourte, A. Neuroimaging outcomes in clinical trials in Alzheimer's disease. J. Nutr. Health Aging 13, 209–212 (2009).

    CAS  PubMed  Google Scholar 

  114. [No authors listed] Prediction of cognitive properties of new drug candidates for neurodegenerative diseases in early clinical development (PHARMA-COG) [online], (2008).

  115. Luxenberg, J. S., Haxby, J. V., Creasey, H., Sundaram, M. & Rapoport, S. I. Rate of ventricular enlargement in dementia of the Alzheimer type correlates with rate of neuropsychological deterioration. Neurology 37, 1135–1140 (1987).

    CAS  PubMed  Google Scholar 

  116. DeCarli, C. et al. Longitudinal changes in lateral ventricular volume in patients with dementia of the Alzheimer type. Neurology 42, 2029–2036 (1992).

    CAS  PubMed  Google Scholar 

  117. Chan, D. et al. Change in rates of cerebral atrophy over time in early-onset Alzheimer's disease: longitudinal MRI study. Lancet 362, 1121–1122 (2003).

    PubMed  Google Scholar 

  118. Schuff, N. et al. Hippocampal Measurements for ADNI [online], (2009).

  119. Hashimoto, M. et al. Does donepezil treatment slow the progression of hippocampal atrophy in patients with Alzheimer's disease? Am. J. Psychiatry 162, 676–682 (2005).

    PubMed  Google Scholar 

  120. Krishnan, K. R. et al. Randomized, placebo-controlled trial of the effects of donepezil on neuronal markers and hippocampal volumes in Alzheimer's disease. Am. J. Psychiatry 160, 2003–2011 (2003).

    PubMed  Google Scholar 

  121. Jack, C. R. Jr et al. Members of the Alzheimer's Disease Cooperative Study (ADCS). Longitudinal MRI findings from the vitamin E and donepezil treatment study for MCI. Neurobiol. Aging 29, 1285–1295 (2008).

    CAS  PubMed  Google Scholar 

  122. Fox, N. C. & Freeborough, P. A. Brain atrophy progression measured from registered serial MRI: validation and application to Alzheimer's disease. J. Magn. Reson. Imaging 7, 1069–1075 (1997).

    CAS  PubMed  Google Scholar 

  123. Kaye, J. A. et al. Asynchronous regional brain volume losses in presymptomatic to moderate AD. J. Alzheimers Dis. 8, 51–56 (2005).

    CAS  PubMed  Google Scholar 

  124. Apostolova, L. G. et al. 3D mapping of Mini-Mental State Examination performance in clinical and pre-clinical Alzheimer's disease. Alzheimer Dis. Assoc. Disord. 20, 224–231 (2006).

    PubMed  Google Scholar 

  125. Apostolova, L. G. & Thompson, P. M. Mapping progressive brain structural changes in early Alzheimer's disease and mild cognitive impairment. Neuropsychologia 46, 1597–1612 (2008).

    PubMed  Google Scholar 

  126. Fotenos, A. F., Snyder, A. Z., Girton, L. E., Morris, J. C. & Buckner, R. L. Normative estimates of cross-sectional and longitudinal brain volume decline in aging and AD. Neurology 64, 1032–1039 (2005).

    CAS  PubMed  Google Scholar 

  127. Jack, C. R. Jr et al. Atrophy rates accelerate in amnestic mild cognitive impairment. Neurology 70, 1740–1752 (2008).

    PubMed  Google Scholar 

  128. Frisoni, G. B., Prestia, A., Rasser, P. E., Bonetti, M. & Thompson, P. M. In vivo mapping of incremental cortical atrophy from incipient to overt Alzheimer's disease. J. Neurol. 256, 916–924 (2009).

    PubMed  Google Scholar 

  129. Frisoni, G. B. et al. Preliminary evidence of validity of the revised criteria for Alzheimer disease diagnosis: report of 2 cases. Alzheimer Dis. Assoc. Disord. doi: 10.1097/WAD.0b013e3181a1fd34.

    Google Scholar 

  130. Bouwman, F. H. et al. New research criteria for the diagnosis of Alzheimer's disease applied in a memory clinic population. Alzheimers Dement. 4, 327–328 (2008).

    Google Scholar 

  131. Landau, S. M. et al. Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol. Aging doi: 10.1016/j.neurobiolaging.2009.07.002.

    PubMed  Google Scholar 

  132. Okello, A. et al. Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study. Neurology 73, 754–760 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  133. Kantarci, K. et al. Alzheimer disease: postmortem neuropathologic correlates of antemortem 1H MR spectroscopy metabolite measurements. Radiology 248, 210–220 (2008).

    PubMed  Google Scholar 

  134. Zhang, Y. et al. White matter damage in frontotemporal dementia and Alzheimer's disease measured by diffusion MRI. Brain 132, 2579–2592 (2009).

    PubMed  PubMed Central  Google Scholar 

  135. [No authors listed] SOPs: harmonization of protocols for the manual tracing of the hippocampus development and validation of a unified standard protocol: an EADC–ADNI joint effort. http://www.centroalzheimer.org/sito/ip_sops_e.php (2008).

  136. Herholz, K. et al. Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. Neuroimage 17, 302–316 (2002).

    CAS  PubMed  Google Scholar 

  137. Miller, G. Alzheimer's biomarker initiative hits its stride. Longitudinal Alzhemer's studies go global. Science 326, 386–389 (2009).

    CAS  PubMed  Google Scholar 

  138. Neary, D. et al. Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology 51, 1546–1554 (1998).

    CAS  PubMed  Google Scholar 

  139. Barnes, J. et al. A meta-analysis of hippocampal atrophy rates in Alzheimer's disease. Neurobiol. Aging 30, 1711–1723 (2009).

    PubMed  Google Scholar 

  140. Henneman, W. J. et al. Hippocampal atrophy rates in Alzheimer disease: added value over whole brain volume measures. Neurology 72, 999–1007 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  141. Sluimer, J. D. et al. Whole-brain atrophy rate in Alzheimer disease: identifying fast progressors. Neurology 70, 1836–1841 (2008).

    CAS  PubMed  Google Scholar 

  142. The Ronald and Nancy Reagan Research Institute of the Alzheimer's Association and National Institute on Aging Working Group. Consensus Report of the Working Group on: “Molecular and Biochemical Markers of Alzheimer's Disease”. Neurobiol. Aging 19, 109–116 (1998).

  143. Lerch, J. P. et al. Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy. Cereb. Cortex 15, 995–1001 (2005).

    PubMed  Google Scholar 

Download references

Acknowledgements

Anna Caroli, Enrica Cavedo, Rossana Ganzola, Marco Lorenzi, Michela Pievani, Annapaola Prestia, Alberto Redolfi and Cristina Scarpazza helped in the literature review, Rossana Ganzola helped in the typesetting of the manuscript, and Alberto Redolfi produced the maps of Figure 4. G. B. Frisoni was supported by FP7 neuGRID, outGRID and IMI Pharma-Cog. N. C. Fox is supported by Medical Research Council grants G0801306 and G0601846, NIH grant U01 AG024904, Alzheimer Research Trust grant ART/RF/2007/1 and the National Institute for Health Research. C. R. Jack is supported by National Institute on Aging grant AG11378 and the Alexander Family Alzheimer's Disease Research Professorship. P. M. Thompson was supported by NIH grants EB007813, EB008281, EB008432, HD050735, AG020098, P41 RR013642 and M01 RR000865.

Author information

Authors and Affiliations

Authors

Ethics declarations

Competing interests

N. C. Fox has received payment for consultancy or for conducting studies from Abbott Laboratories, Elan Pharmaceuticals, Eisai, Eli Lilly, GE Healthcare, IXICO, Lundbeck, Pfizer, Sanofi-Aventis and Wyeth Pharmaceuticals. The other authors declare no competing interests.

Supplementary information

Supplementary Table 1

Rates of brain atrophy and ventricular enlargement in Alzheimer disease. (DOC 117 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Frisoni, G., Fox, N., Jack, C. et al. The clinical use of structural MRI in Alzheimer disease. Nat Rev Neurol 6, 67–77 (2010). https://doi.org/10.1038/nrneurol.2009.215

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrneurol.2009.215

This article is cited by

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research