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Biomarkers for Alzheimer’s Disease and Frontotemporal Lobar Degeneration: Imaging

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Neurodegenerative Diseases

Abstract

In recent years, our understanding of neurodegenerative dementias has translated into a change in the clinical approach to patients presenting with impairments in cognition and behavior. The diagnosis of different forms of neurodegenerative dementias is currently based not only on their clinical and neuropsychological characterization but also on the use of biomarkers. Advances in neuroimaging techniques, particularly magnetic resonance imaging (MRI), have strongly contributed not only in increasing our understanding of clinical and pathophysiological aspects of dementias but also in improving the diagnostic confidence in clinical settings. MRI, thanks to its ability to image in vivo soft tissues noninvasively and with detailed anatomical resolution, shows high sensitivity in detecting the presence and extension of macroscopic brain abnormalities. In this view, as discussed below, MRI plays the unique role of excluding alternative diagnoses that may mimic a neurodegenerative form of cognitive decline.

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References

  1. McGinnis SM. Neuroimaging in neurodegenerative dementias. Semin Neurol. 2012;32(4):347–60.

    PubMed  Google Scholar 

  2. Bozzali M, Padovani A, Caltagirone C, Borroni B. Regional grey matter loss and brain disconnection across Alzheimer disease evolution. Curr Med Chem. 2011;18(16):2452–8.

    Article  PubMed  CAS  Google Scholar 

  3. Cummings JL. Toward a molecular neuropsychiatry of neurodegenerative diseases. Ann Neurol. 2003;54(2):147–54.

    Article  PubMed  CAS  Google Scholar 

  4. Gili T, Cercignani M, Serra L, Perri R, Giove F, Maraviglia B, Caltagirone C, Bozzali M. Regional brain atrophy and functional disconnection across Alzheimer’s disease evolution. J Neurol Neurosurg Psychiatry. 2011;82(1):58–66.

    Article  PubMed  CAS  Google Scholar 

  5. Borroni B, Alberici A, Cercignani M, Premi E, Serra L, Cerini C, et al. Granulin mutation drives brain damage and reorganization from preclinical to symptomatic FTLD. Neurobiol Aging. 2012;33(10):2506–20.

    Article  PubMed  CAS  Google Scholar 

  6. Sosa-Ortiz AL, Acosta-Castillo I, Prince MJ. Epidemiology of dementias and Alzheimer’s disease. Arch Med Res. 2012;43(8):600–8.

    Article  PubMed  Google Scholar 

  7. Braak H, Braak E. Staging of Alzheimer’s disease-related neurofibrillary changes. Neurobiol Aging. 1995;16(3):271–8.

    Article  PubMed  CAS  Google Scholar 

  8. Markesbery WR. Neuropathologic alterations in mild cognitive impairment: a review. J Alzheimers Dis. 2010;19(1):221–8.

    PubMed Central  PubMed  Google Scholar 

  9. Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, Gamst A, Holtzman DM, Jagust WJ, Petersen RC, Snyder PJ, Carrillo MC, Thies B, Phelps CH. 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):270–9.

    Article  PubMed Central  PubMed  Google Scholar 

  10. Scheltens P, Leys D, Barkhof F, Huglo D, Weinstein HC, Vermersch P, Kuiper M, Steinling M, Wolters EC, Valk J. 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):967–72.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  11. Wahlund LO, Barkhof F, Fazekas F, Bronge L, Augustin M, Sjögren M, et al.; European Task Force on Age-Related White Matter Changes. A new rating scale for age-related white matter changes applicable to MRI and CT. Stroke. 2001;32(6):1318–22.

    Google Scholar 

  12. Ridha BH, Barnes J, van de Pol LA, Schott JM, Boyes RG, Siddique MM, et al. Application of automated medial temporal lobe atrophy scale to Alzheimer disease. Arch Neurol. 2007;64(6):849–54.

    Article  PubMed  Google Scholar 

  13. Fazekas F, Chawluk JB, Alvavi A, Hurtig HI, Zimmerman RA. MR signal abnormalities at 1.5T in Alzheimer’s disease and normal aging. AJR Am J Roentgenol. 1987;8:421–6.

    Google Scholar 

  14. Seab JP, Jagust WJ, Wong ST, Roos MS, Reed BR, Budinger TF. Quantitative NMR measurements of hippocampal atrophy in Alzheimer’s disease. Magn Reson Med. 1988;8(2):200–8.

    Article  PubMed  CAS  Google Scholar 

  15. Convit A, De Leon MJ, Tarshish C, De Santi S, Tsui W, Rusinek H, George A. Specific hippocampal volume reductions in individuals at risk for Alzheimer’s disease. Neurobiol Aging. 1997;18(2):131–8.

    Article  PubMed  CAS  Google Scholar 

  16. Jack Jr CR, Petersen RC, Xu YC, O’Brien PC, Smith GE, Ivnik RJ, Boeve BF, Waring SC, Tangalos EG, Kokmen E. Prediction of AD with MRI-based hippocampal volume in mild cognitive impairment. Neurology. 1999;52(7):1397–403.

    Article  PubMed Central  PubMed  Google Scholar 

  17. Frisoni GB, Jack CR. Harmonization of magnetic resonance-based manual hippocampal segmentation: a mandatory step for wide clinical use. Alzheimers Dement. 2011;7(2):171–4.

    Article  PubMed  Google Scholar 

  18. Ashburner J, Friston KJ. Voxel-based morphometry–the methods. Neuroimage. 2000;11(6):805–21.

    Article  PubMed  CAS  Google Scholar 

  19. Bozzali M, Filippi M, Magnani G, Cercignani M, Franceschi M, Schiatti E, et al. The contribution of voxel-based morphometry in staging patients with mild cognitive impairment. Neurology. 2006;67(3):453–60.

    Article  PubMed  CAS  Google Scholar 

  20. Serra L, Cercignani M, Lenzi D, Perri R, Fadda L, Caltagirone C, et al. Grey and white matter changes at different stages of Alzheimer’s disease. J Alzheimers Dis. 2010;19(1):147–59.

    PubMed  Google Scholar 

  21. Serra L, Fadda L, Perri R, Spanò B, Marra C, Castelli D, et al. Constructional apraxia as a distinctive cognitive and structural brain feature of pre-senile Alzheimer’s disease. J Alzheimers Dis. 2014;38:391–402.

    PubMed  Google Scholar 

  22. Serra L, Perri R, Cercignani M, Spanò B, Fadda L, Marra C, et al. Are the behavioral symptoms of Alzheimer’s disease directly associated with neurodegeneration? J Alzheimers Dis. 2010;21(2):627–39.

    PubMed  Google Scholar 

  23. Serra L, Cercignani M, Petrosini L, Basile B, Perri R, Fadda L, et al. Neuroanatomical correlates of cognitive reserve in Alzheimer disease. Rejuvenation Res. 2011;14(2):143–51.

    Article  PubMed  Google Scholar 

  24. Serra L, Giulietti G, Cercignani M, Spanò B, Torso M, Castelli D, et al. Mild cognitive impairment: same identity for different entities. J Alzheimers Dis. 2013;33(4):1157–65.

    PubMed  Google Scholar 

  25. Basser PJ, Jones DK. Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review. NMR Biomed. 2002;15(7–8):456–67.

    Article  PubMed  Google Scholar 

  26. Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage. 2006;31(4):1487–505.

    Article  PubMed  Google Scholar 

  27. Jones DK. Studying connections in the living human brain with diffusion MRI. Cortex. 2008;44(8):936–52.

    Article  PubMed  Google Scholar 

  28. Liu Y, Spulber G, Lehtimäki KK, Könönen M, Hallikainen I, Gröhn H, et al. Diffusion tensor imaging and tract-based spatial statistics in Alzheimer’s disease and mild cognitive impairment. Neurobiol Aging. 2011;32(9):1558–71.

    Article  PubMed  Google Scholar 

  29. Serra L, Cercignani M, Basile B, Spanò B, Perri R, Fadda L, et al. White matter damage along the uncinate fasciculus contributes to cognitive decline in AD and DLB. Curr Alzheimer Res. 2012;9(3):326–33.

    Article  PubMed  CAS  Google Scholar 

  30. Bozzali M, Giulietti G, Basile B, Serra L, Spanò B, Perri R, et al. Damage to the cingulum contributes to Alzheimer’s disease pathophysiology by deafferentation mechanism. Hum Brain Mapp. 2012;33(6):1295–308.

    Article  PubMed  Google Scholar 

  31. Bozzali M, Parker GJ, Serra L, Embleton K, Gili T, Perri R, et al. Anatomical connectivity mapping: a new tool to assess brain disconnection in Alzheimer’s disease. Neuroimage. 2011;54(3):2045–51.

    Article  PubMed  Google Scholar 

  32. Bozzali M, Parker GJ, Spanò B, Serra L, Giulietti G, Perri R, et al. Brain tissue modifications induced by cholinergic therapy in Alzheimer’s disease. Hum Brain Mapp. 2013;34(12):3158–67.

    Article  PubMed  Google Scholar 

  33. Peters F, Collette F, Degueldre C, Sterpenich V, Majerus S, Salmon E. The neural correlates of verbal short-term memory in Alzheimer’s disease: an fMRI study. Brain. 2009;132(7):1833–46.

    Article  PubMed  Google Scholar 

  34. Golby A, Silverberg G, Race E, Gabrieli S, O’Shea J, Knierim K, et al. Memory encoding in Alzheimer’s disease: an fMRI study of explicit and implicit memory. Brain. 2005;128(4):773–87.

    Article  PubMed  Google Scholar 

  35. Pihlajamäki M, Jauhiainen AM, Soininen H. Structural and functional MRI in mild cognitive impairment. Curr Alzheimer Res. 2009;6(2):179–85.

    Article  PubMed  Google Scholar 

  36. Lenzi D, Serra L, Perri R, Pantano P, Lenzi GL, Paulesu E, et al. Single domain amnestic MCI: a multiple cognitive domains fMRI investigation. Neurobiol Aging. 2011;32(9):1542–57.

    Article  PubMed  CAS  Google Scholar 

  37. Greicius MD, Krasnow B, Reiss AL, Menon V. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci U S A. 2003;100(1):253–8.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  38. Greicius MD, Supekar K, Menon V, Dougherty RF. Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb Cortex. 2009;19(1):72–8.

    Article  PubMed Central  PubMed  Google Scholar 

  39. Phelps ME. PET: the merging of biology and imaging into molecular imaging. J Nucl Med. 2000;41(4):661–81.

    PubMed  CAS  Google Scholar 

  40. 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 

  41. Knopman DS. Diagnostic tests for Alzheimer disease: FDG-PET imaging is a player in search of a role. Neurol Clin Pract. 2012;2(2):151–3.

    Article  PubMed Central  PubMed  Google Scholar 

  42. Scherfler C, Schwarz J, Antonini A, Grosset D, Valldeoriola F, Marek K, et al. Role of DAT-SPECT in the diagnostic work up of parkinsonism. Mov Disord. 2007;22(9):1229–38.

    Article  PubMed  Google Scholar 

  43. Hardy J, Selkoe DJ. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science. 2002;297(5580):353–6.

    Article  PubMed  CAS  Google Scholar 

  44. Rowe CC, Villemagne VL. Amyloid imaging with PET in early Alzheimer disease diagnosis. Med Clin North Am. 2013;97(3):377–98.

    Article  PubMed  Google Scholar 

  45. Visser PJ, Vos S, van Rossum I, Scheltens P. Comparison of International Working Group criteria and National Institute on Aging-Alzheimer’s Association criteria for Alzheimer’s disease. Alzheimers Dement. 2012;8(6):560–3.

    Article  PubMed  Google Scholar 

  46. Villemagne VL, Rowe CC, Macfarlane S, Novakovic KE, Masters CL. Imaginem oblivionis: the prospects of neuroimaging for early detection of Alzheimer’s disease. J Clin Neurosci. 2005;12(3):221–30.

    Article  PubMed  Google Scholar 

  47. Cohen AD, Rabinovici GD, Mathis CA, Jagust WJ, Klunk WE, Ikonomovic MD. Using Pittsburgh Compound B for in vivo PET imaging of fibrillar amyloid-beta. Adv Pharmacol. 2012;64:27–81.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  48. Ikonomovic MD, Klunk WE, Abrahamson EE, Mathis CA, Price JC, Tsopelas ND, et al. Post-mortem correlates of in vivo PiB-PET amyloid imaging in a typical case of Alzheimer’s disease. Brain. 2008;131(6):1630–45.

    Article  PubMed Central  PubMed  Google Scholar 

  49. Rabinovici GD, Miller BL. Frontotemporal lobar degeneration: epidemiology, pathophysiology, diagnosis and management. CNS Drugs. 2010;24(5):375–98.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  50. Whitwell JL, Josephs KA, Avula R, Tosakulwong N, Weigand SD, Senjem ML, et al. Altered functional connectivity in asymptomatic MAPT subjects: a comparison to bvFTD. Neurology. 2011;77(9):866–74.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  51. Josephs KA, Hodges JR, Snowden JS, Mackenzie IR, Neumann M, Mann DM, Dickson DW. Neuropathological background of phenotypical variability in frontotemporal dementia. Acta Neuropathol. 2011;122(2):137–53.

    Article  PubMed Central  PubMed  Google Scholar 

  52. Whitwell JL, Josephs KA. Neuroimaging in frontotemporal lobar degeneration–predicting molecular pathology. Nat Rev Neurol. 2012;8(3):131–42.

    Article  PubMed  CAS  Google Scholar 

  53. Neumann M, Sampathu DM, Kwong LK, Truax AC, Micsenyi MC, Chou TT, et al. Ubiquitinated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Science. 2006;314(5796):130–3.

    Article  PubMed  CAS  Google Scholar 

  54. Neumann M, Rademakers R, Roeber S, Baker M, Kretzschmar HA, Mackenzie IR. A new subtype of frontotemporal lobar degeneration with FUS pathology. Brain. 2009;132(11):2922–31.

    Article  PubMed Central  PubMed  Google Scholar 

  55. Hutton M, Lendon CL, Rizzu P, Baker M, Froelich S, Houlden H, et al. Association of missense and 5′-splice-site mutations in tau with the inherited dementia FTDP-17. Nature. 1998;393(6686):702–5.

    Article  PubMed  CAS  Google Scholar 

  56. Cruts M, Gijselinck I, van der Zee J, Engelborghs S, Wils H, Pirici D, et al. Null mutations in progranulin cause ubiquitin-positive frontotemporal dementia linked to chromosome 17q21. Nature. 2006;442(7105):920–4.

    Article  PubMed  CAS  Google Scholar 

  57. Renton AE, Majounie E, Waite A, Simón-Sánchez J, Rollinson S, Gibbs JR, et al. A hexanucleotide repeat expansion in C9ORF72 is the cause of chromosome 9p21-linked ALS-FTD. Neuron. 2011;72(2):257–68.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  58. Pick A. Ubeer die Beziehungen der senile Hirnatrophie zur aphasie. Prager Med Wochenschr. 1892;17:165–7.

    Google Scholar 

  59. Mesulam MM. Slowly progressive aphasia without generalized dementia. Ann Neurol. 1982;11(6):592–8.

    Article  PubMed  CAS  Google Scholar 

  60. Mesulam MM, Weintraub S. Spectrum of primary progressive aphasia. Baillieres Clin Neurol. 1992;1(3):583–609.

    PubMed  CAS  Google Scholar 

  61. Warrington EK. The selective impairment of semantic memory. Q J Exp Psychol. 1975;27(4):635–57.

    Article  PubMed  CAS  Google Scholar 

  62. Snowden JS, Goulding PJ, Neary D. Semantic dementia: a form of circumscribed cerebral atrophy. Behav Neurol. 1989;2:167–82.

    Google Scholar 

  63. Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, et al. Classification of primary progressive aphasia and its variants. Neurology. 2011;76(11):1006–14.

    Article  PubMed Central  PubMed  Google Scholar 

  64. Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, et al. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain. 2011;134(9):2456–77.

    Article  PubMed Central  PubMed  Google Scholar 

  65. Rohrer JD, Paviour D, Bronstein AM, O’Sullivan SS, Lees A, Warren JD. Progressive supranuclear palsy syndrome presenting as progressive nonfluent aphasia: a neuropsychological and neuroimaging analysis. Mov Disord. 2010;25(2):179–88.

    Article  PubMed  Google Scholar 

  66. 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):335–46.

    Article  PubMed Central  PubMed  Google Scholar 

  67. Seeley WW, Crawford RK, Zhou J, Miller BL, Greicius MD. Neurodegenerative diseases target large-scale human brain networks. Neuron. 2009;62(1):42–52.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  68. Zhang Y, Tartaglia MC, Schuff N, Chiang GC, Ching C, Rosen HJ, et al. MRI signatures of brain macrostructural atrophy and microstructural degradation in frontotemporal lobar degeneration subtypes. J Alzheimers Dis. 2013;33(2):431–44.

    PubMed Central  PubMed  Google Scholar 

  69. Rohrer JD. Structural brain imaging in frontotemporal dementia. Biochim Biophys Acta. 2012;1822(3):325–32.

    Article  PubMed  CAS  Google Scholar 

  70. Hodges JR, Patterson K. Semantic dementia: a unique clinicopathological syndrome. Lancet Neurol. 2007;6(11):1004–14.

    Article  PubMed  CAS  Google Scholar 

  71. Schroeter ML, Raczka K, Neumann J, von Cramon DY. Neural networks in frontotemporal dementia–a meta-analysis. Neurobiol Aging. 2008;29(3):418–26.

    Article  PubMed  Google Scholar 

  72. Whitwell JL, Przybelski SA, Weigand SD, Ivnik RJ, Vemuri P, Gunter JL, et al. Distinct anatomical subtypes of the behavioural variant of frontotemporal dementia: a cluster analysis study. Brain. 2009;132(Pt 11):2932–46.

    Article  PubMed Central  PubMed  Google Scholar 

  73. Rosen HJ, Allison SC, Schauer GF, Gomo-Tempini ML, Weiner MW, Miller BL. Neuroanatomical correlates of behavioural disorders in dementia. Brain. 2005;128:2612–25.

    Article  PubMed Central  PubMed  Google Scholar 

  74. Zhou J, Greicius MD, Gennatas ED, Growdon ME, Jang JY, Rabinovici GD, et al. Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer’s disease. Brain. 2010;133(5):1352–67.

    Article  PubMed Central  PubMed  Google Scholar 

  75. Day GS, Farb NA, Tang-Wai DF, Masellis M, Black SE, Freedman M, et al. Salience network resting-state activity: prediction of frontotemporal dementia progression. JAMA Neurol. 2013;70:1249–53.

    PubMed  Google Scholar 

  76. Rytty R, Nikkinen J, Paavola L, Abou Elseoud A, Moilanen V, Visuri A, et al. GroupICA dual regression analysis of resting state networks in a behavioral variant of frontotemporal dementia. Front Hum Neurosci. 2013;7:461.

    Article  PubMed Central  PubMed  Google Scholar 

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Bozzali, M., Serra, L. (2014). Biomarkers for Alzheimer’s Disease and Frontotemporal Lobar Degeneration: Imaging. In: Galimberti, D., Scarpini, E. (eds) Neurodegenerative Diseases. Springer, London. https://doi.org/10.1007/978-1-4471-6380-0_10

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