Skip to main content
SpringerLink
Log in

Imaging Neuroinflammation: Quantification of Astrocytosis in a Multitracer PET Approach

  • Protocol
  • First Online:
Biomarkers for Alzheimer’s Disease Drug Development

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1750))

Abstract

The recent progress in the development of in vivo biomarkers is rapidly changing how neurodegenerative diseases are conceptualized and diagnosed, and how clinical trials are designed today. Alzheimer’s disease (AD)—the most common neurodegenerative disorder—is characterized by a complex neuropathology involving the deposition of extracellular amyloid-β (Aβ) plaques and intracellular neurofibrillary tangles (NFT) of hyperphosphorylated tau proteins, accompanied by the activation of glial cells—astrocytes and microglia—and neuroinflammatory responses, leading to neurodegeneration and cognitive dysfunction. An increasing diversity of positron emission tomography (PET) imaging radiotracers are available to selectively target the different pathophysiological processes of AD. Along with the success of Aβ PET and the more recent tau PET imaging, there is also a great interest to develop PET tracers to image glial activation and neuroinflammation. While most research to date has focused on imaging microgliosis, recent studies using 11C-deuterium-l-deprenyl (11C-DED) PET imaging suggest that astrocytosis may be present from very early stages of disease development in AD. This chapter provides a detailed description of the practical approach used for the analysis of 11C-DED PET imaging data in a multitracer PET paradigm including 11C-Pittsburgh compound B (11C-PiB) and 18F-fluorodeoxyglucose (18F-FDG). The multitracer PET approach allows investigating the comparative regional and temporal patterns of in vivo brain astrocytosis, fibrillar Aβ deposition, and glucose metabolism in patients at different stages of disease progression. This chapter attempts to stimulate further research in the field, including the development of novel PET tracers that may allow visualizing different aspects of the complex astrocytic and microglial responses in neurodegenerative diseases. Progress in the field will contribute to the incorporation of PET imaging of glial activation and neuroinflammation as biomarkers with clinical application, and motivate further investigation on glial cells as therapeutic targets in AD and other neurodegenerative diseases.

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

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Mattsson N, Carrillo MC, Dean RA, Devous MD Sr, Nikolcheva T, Pesini P, Salter H, Potter WZ, Sperling RS, Bateman RJ, Bain LJ, Liu E (2015) Revolutionizing Alzheimer’s disease and clinical trials through biomarkers. Alzheimers Dement (Amst) 1(4):412–419. https://doi.org/10.1016/j.dadm.2015.09.001

    Article  Google Scholar 

  2. Braak H, Braak E (1991) Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 82(4):239–259

    Article  CAS  PubMed  Google Scholar 

  3. Hardy J, Selkoe DJ (2002) The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science 297(5580):353–356. https://doi.org/10.1126/science.1072994

    Article  PubMed  CAS  Google Scholar 

  4. Jack CR Jr, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, Shaw LM, Vemuri P, Wiste HJ, Weigand SD, Lesnick TG, Pankratz VS, Donohue MC, Trojanowski JQ (2013) Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 12(2):207–216. https://doi.org/10.1016/S1474-4422(12)70291-0

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Jack CR Jr, Wiste HJ, Weigand SD, Knopman DS, Lowe V, Vemuri P, Mielke MM, Jones DT, Senjem ML, Gunter JL, Gregg BE, Pankratz VS, Petersen RC (2013) Amyloid-first and neurodegeneration-first profiles characterize incident amyloid PET positivity. Neurology 81(20):1732–1740. https://doi.org/10.1212/01.wnl.0000435556.21319.e4

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Sperling R, Mormino E, Johnson K (2014) The evolution of preclinical Alzheimer’s disease: implications for prevention trials. Neuron 84(3):608–622. https://doi.org/10.1016/j.neuron.2014.10.038

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Heneka MT, Carson MJ, El Khoury J, Landreth GE, Brosseron F, Feinstein DL, Jacobs AH, Wyss-Coray T, Vitorica J, Ransohoff RM, Herrup K, Frautschy SA, Finsen B, Brown GC, Verkhratsky A, Yamanaka K, Koistinaho J, Latz E, Halle A, Petzold GC, Town T, Morgan D, Shinohara ML, Perry VH, Holmes C, Bazan NG, Brooks DJ, Hunot S, Joseph B, Deigendesch N, Garaschuk O, Boddeke E, Dinarello CA, Breitner JC, Cole GM, Golenbock DT, Kummer MP (2015) Neuroinflammation in Alzheimer’s disease. Lancet Neurol 14(4):388–405. https://doi.org/10.1016/S1474-4422(15)70016-5

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. De Strooper B, Karran E (2016) The cellular phase of Alzheimer’s disease. Cell 164(4):603–615. https://doi.org/10.1016/j.cell.2015.12.056

    Article  PubMed  CAS  Google Scholar 

  9. Acosta C, Anderson HD, Anderson CM (2017) Astrocyte dysfunction in Alzheimer disease. J Neurosci Res 95:2430. https://doi.org/10.1002/jnr.24075

    Article  PubMed  CAS  Google Scholar 

  10. Verkhratsky A, Marutle A, Rodriguez-Arellano JJ, Nordberg A (2015) Glial asthenia and functional paralysis: a new perspective on neurodegeneration and Alzheimer’s disease. The Neuroscientist 21(5):552–568. https://doi.org/10.1177/1073858414547132

    Article  PubMed  CAS  Google Scholar 

  11. Thal DR (2012) The role of astrocytes in amyloid beta-protein toxicity and clearance. Exp Neurol 236(1):1–5. https://doi.org/10.1016/j.expneurol.2012.04.021

    Article  PubMed  CAS  Google Scholar 

  12. Chung WS, Welsh CA, Barres BA, Stevens B (2015) Do glia drive synaptic and cognitive impairment in disease? Nat Neurosci 18(11):1539–1545. https://doi.org/10.1038/nn.4142

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Murray ME, Graff-Radford NR, Ross OA, Petersen RC, Duara R, Dickson DW (2011) Neuropathologically defined subtypes of Alzheimer’s disease with distinct clinical characteristics: a retrospective study. Lancet Neurol 10(9):785–796. https://doi.org/10.1016/S1474-4422(11)70156-9

    Article  PubMed  PubMed Central  Google Scholar 

  14. Jones T, Townsend D (2017) History and future technical innovation in positron emission tomography. J Med Imaging (Bellingham) 4(1):011013. https://doi.org/10.1117/1.JMI.4.1.011013

    Article  Google Scholar 

  15. Turkheimer FE, Veronese M, Dunn J (2014) Experimental design and practical data analysis in positron emission tomography. King’s College, London

    Google Scholar 

  16. Pike VW (2009) PET radiotracers: crossing the blood-brain barrier and surviving metabolism. Trends Pharmacol Sci 30(8):431–440. https://doi.org/10.1016/j.tips.2009.05.005

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH (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. https://doi.org/10.1016/j.jalz.2011.03.005

    Article  PubMed  PubMed Central  Google Scholar 

  18. Dubois B, Feldman HH, Jacova C, Hampel H, Molinuevo JL, Blennow K, DeKosky ST, Gauthier S, Selkoe D, Bateman R, Cappa S, Crutch S, Engelborghs S, Frisoni GB, Fox NC, Galasko D, Habert MO, Jicha GA, Nordberg A, Pasquier F, Rabinovici G, Robert P, Rowe C, Salloway S, Sarazin M, Epelbaum S, de Souza LC, Vellas B, Visser PJ, Schneider L, Stern Y, Scheltens P, Cummings JL (2014) Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol 13(6):614–629. https://doi.org/10.1016/S1474-4422(14)70090-0

    Article  PubMed  Google Scholar 

  19. Saint-Aubert L, Lemoine L, Chiotis K, Leuzy A, Rodriguez-Vieitez E, Nordberg A (2017) Tau PET imaging: present and future directions. Mol Neurodegener 12(1):19. https://doi.org/10.1186/s13024-017-0162-3

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Jacobs AH, Tavitian B, INMiND Consortium (2012) Noninvasive molecular imaging of neuroinflammation. J Cereb Blood Flow Metab 32(7):1393–1415. https://doi.org/10.1038/jcbfm.2012.53

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Albrecht DS, Granziera C, Hooker JM, Loggia ML (2016) In vivo imaging of human neuroinflammation. ACS Chem Neurosci 7(4):470–483. https://doi.org/10.1021/acschemneuro.6b00056

    Article  PubMed  CAS  Google Scholar 

  22. Varrone A, Nordberg A. (2015) Molecular imaging of neuroinflammation in Alzheimer’s disease. Clin Transl Imaging 3:437–447

    Article  Google Scholar 

  23. Burda JE, Sofroniew MV (2014) Reactive gliosis and the multicellular response to CNS damage and disease. Neuron 81(2):229–248. https://doi.org/10.1016/j.neuron.2013.12.034

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Hamby ME, Sofroniew MV (2010) Reactive astrocytes as therapeutic targets for CNS disorders. Neurotherapeutics 7(4):494–506. https://doi.org/10.1016/j.nurt.2010.07.003

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Stefaniak J, O’Brien J (2016) Imaging of neuroinflammation in dementia: a review. J Neurol Neurosurg Psychiatry 87(1):21–28. https://doi.org/10.1136/jnnp-2015-311336

    Article  PubMed  Google Scholar 

  26. Varley J, Brooks DJ, Edison P (2015) Imaging neuroinflammation in Alzheimer’s disease and other dementias: recent advances and future directions. Alzheimers Dement 11(9):1110–1120. https://doi.org/10.1016/j.jalz.2014.08.105

    Article  PubMed  Google Scholar 

  27. Lagarde J, Sarazin M, Bottlaender M (2017) In vivo PET imaging of neuroinflammation in Alzheimer’s disease. J Neural Transm (Vienna). https://doi.org/10.1007/s00702-017-1731-x

  28. Lavisse S, Guillermier M, Herard AS, Petit F, Delahaye M, Van Camp N, Ben Haim L, Lebon V, Remy P, Dolle F, Delzescaux T, Bonvento G, Hantraye P, Escartin C (2012) Reactive astrocytes overexpress TSPO and are detected by TSPO positron emission tomography imaging. J Neurosci 32(32):10809–10818. https://doi.org/10.1523/JNEUROSCI.1487-12.2012

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  29. Cosenza-Nashat M, Zhao ML, Suh HS, Morgan J, Natividad R, Morgello S, Lee SC (2009) Expression of the translocator protein of 18 kDa by microglia, macrophages and astrocytes based on immunohistochemical localization in abnormal human brain. Neuropathol Appl Neurobiol 35(3):306–328. https://doi.org/10.1111/j.1365-2990.2008.01006.x

    Article  PubMed  CAS  Google Scholar 

  30. Turkheimer FE, Rizzo G, Bloomfield PS, Howes O, Zanotti-Fregonara P, Bertoldo A, Veronese M (2015) The methodology of TSPO imaging with positron emission tomography. Biochem Soc Trans 43(4):586–592. https://doi.org/10.1042/BST20150058

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Parker CA, Nabulsi N, Holden D, Lin SF, Cass T, Labaree D, Kealey S, Gee AD, Husbands SM, Quelch D, Carson RE, Nutt DJ, Huang Y, Tyacke RJ (2014) Evaluation of 11C-BU99008, a PET ligand for the imidazoline2 binding sites in rhesus brain. J Nucl Med 55(5):838–844. https://doi.org/10.2967/jnumed.113.131854

    Article  PubMed  CAS  Google Scholar 

  32. Wyss MT, Magistretti PJ, Buck A, Weber B (2011) Labeled acetate as a marker of astrocytic metabolism. J Cereb Blood Flow Metab 31(8):1668–1674. https://doi.org/10.1038/jcbfm.2011.84

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Fowler JS, Logan J, Volkow ND, Wang GJ (2005) Translational neuroimaging: positron emission tomography studies of monoamine oxidase. Mol Imaging Biol 7(6):377–387. https://doi.org/10.1007/s11307-005-0016-1

    Article  PubMed  Google Scholar 

  34. Fowler JS, MacGregor RR, Wolf AP, Arnett CD, Dewey SL, Schlyer D, Christman D, Logan J, Smith M, Sachs H et al (1987) Mapping human brain monoamine oxidase A and B with 11C-labeled suicide inactivators and PET. Science 235(4787):481–485

    Article  CAS  PubMed  Google Scholar 

  35. Ekblom J, Jossan SS, Bergstrom M, Oreland L, Walum E, Aquilonius SM (1993) Monoamine oxidase-B in astrocytes. Glia 8(2):122–132. https://doi.org/10.1002/glia.440080208

    Article  PubMed  CAS  Google Scholar 

  36. Ekblom J, Jossan SS, Oreland L, Walum E, Aquilonius SM (1994) Reactive gliosis and monoamine oxidase B. J Neural Transm Suppl 41:253–258

    PubMed  CAS  Google Scholar 

  37. Levitt P, Pintar JE, Breakefield XO (1982) Immunocytochemical demonstration of monoamine oxidase B in brain astrocytes and serotonergic neurons. Proc Natl Acad Sci U S A 79(20):6385–6389

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Jossan SS, Ekblom J, Aquilonius SM, Oreland L (1994) Monoamine oxidase-B in motor cortex and spinal cord in amyotrophic lateral sclerosis studied by quantitative autoradiography. J Neural Transm Suppl 41:243–248

    PubMed  CAS  Google Scholar 

  39. Lemoine L, Saint-Aubert L, Nennesmo I, Gillberg PG, Nordberg A (2017) Cortical laminar tau deposits and activated astrocytes in Alzheimer’s disease visualised by 3H-THK5117 and 3H-deprenyl autoradiography. Sci Rep 7:45496. https://doi.org/10.1038/srep45496

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Marutle A, Gillberg PG, Bergfors A, Yu W, Ni R, Nennesmo I, Voytenko L, Nordberg A (2013) (3)H-deprenyl and (3)H-PIB autoradiography show different laminar distributions of astroglia and fibrillar beta-amyloid in Alzheimer brain. J Neuroinflammation 10:90. https://doi.org/10.1186/1742-2094-10-90

  41. Saura J, Luque JM, Cesura AM, Da Prada M, Chan-Palay V, Huber G, Loffler J, Richards JG (1994) Increased monoamine oxidase B activity in plaque-associated astrocytes of Alzheimer brains revealed by quantitative enzyme radioautography. Neuroscience 62(1):15–30

    Article  CAS  PubMed  Google Scholar 

  42. Gulyas B, Pavlova E, Kasa P, Gulya K, Bakota L, Varszegi S, Keller E, Horvath MC, Nag S, Hermecz I, Magyar K, Halldin C (2011) Activated MAO-B in the brain of Alzheimer patients, demonstrated by [11C]-L-deprenyl using whole hemisphere autoradiography. Neurochem Int 58(1):60–68. https://doi.org/10.1016/j.neuint.2010.10.013

    Article  PubMed  CAS  Google Scholar 

  43. Fowler JS, Wang GJ, Logan J, Xie S, Volkow ND, MacGregor RR, Schlyer DJ, Pappas N, Alexoff DL, Patlak C et al (1995) Selective reduction of radiotracer trapping by deuterium substitution: comparison of carbon-11-L-deprenyl and carbon-11-deprenyl-D2 for MAO B mapping. J Nucl Med 36(7):1255–1262

    PubMed  CAS  Google Scholar 

  44. Fowler JS, Wolf AP, MacGregor RR, Dewey SL, Logan J, Schlyer DJ, Langstrom B (1988) Mechanistic positron emission tomography studies: demonstration of a deuterium isotope effect in the monoamine oxidase-catalyzed binding of [11C]L-deprenyl in living baboon brain. J Neurochem 51(5):1524–1534

    Article  CAS  PubMed  Google Scholar 

  45. Santillo AF, Gambini JP, Lannfelt L, Langstrom B, Ulla-Marja L, Kilander L, Engler H (2011) In vivo imaging of astrocytosis in Alzheimer’s disease: an (1)(1)C-L-deuteriodeprenyl and PIB PET study. Eur J Nucl Med Mol Imaging 38(12):2202–2208. https://doi.org/10.1007/s00259-011-1895-9

    Article  PubMed  Google Scholar 

  46. Carter SF, Scholl M, Almkvist O, Wall A, Engler H, Langstrom B, Nordberg A (2012) Evidence for astrocytosis in prodromal Alzheimer disease provided by 11C-deuterium-L-deprenyl: a multitracer PET paradigm combining 11C-Pittsburgh compound B and 18F-FDG. J Nucl Med 53(1):37–46. https://doi.org/10.2967/jnumed.110.087031

    Article  PubMed  CAS  Google Scholar 

  47. Johansson A, Engler H, Blomquist G, Scott B, Wall A, Aquilonius SM, Langstrom B, Askmark H (2007) Evidence for astrocytosis in ALS demonstrated by [11C](L)-deprenyl-D2 PET. J Neurol Sci 255(1–2):17–22. https://doi.org/10.1016/j.jns.2007.01.057

    Article  PubMed  CAS  Google Scholar 

  48. Engler H, Lundberg PO, Ekbom K, Nennesmo I, Nilsson A, Bergstrom M, Tsukada H, Hartvig P, Langstrom B (2003) Multitracer study with positron emission tomography in Creutzfeldt-Jakob disease. Eur J Nucl Med Mol Imaging 30(1):85–95. https://doi.org/10.1007/s00259-002-1008-x

    Article  PubMed  CAS  Google Scholar 

  49. Engler H, Nennesmo I, Kumlien E, Gambini JP, Lundberg P, Savitcheva I, Langstrom B (2012) Imaging astrocytosis with PET in Creutzfeldt-Jakob disease: case report with histopathological findings. Int J Clin Exp Med 5(2):201–207

    PubMed  PubMed Central  CAS  Google Scholar 

  50. Choo IL, Carter SF, Scholl ML, Nordberg A (2014) Astrocytosis measured by (1)(1)C-deprenyl PET correlates with decrease in gray matter density in the parahippocampus of prodromal Alzheimer’s patients. Eur J Nucl Med Mol Imaging 41(11):2120–2126. https://doi.org/10.1007/s00259-014-2859-7

    Article  PubMed  CAS  Google Scholar 

  51. Rodriguez-Vieitez E, Carter SF, Chiotis K, Saint-Aubert L, Leuzy A, Scholl M, Almkvist O, Wall A, Langstrom B, Nordberg A (2016) Comparison of early-phase 11C-deuterium-l-Deprenyl and 11C-Pittsburgh compound B PET for assessing brain perfusion in Alzheimer disease. J Nucl Med 57(7):1071–1077. https://doi.org/10.2967/jnumed.115.168732

    Article  PubMed  CAS  Google Scholar 

  52. Scholl M, Carter SF, Westman E, Rodriguez-Vieitez E, Almkvist O, Thordardottir S, Wall A, Graff C, Langstrom B, Nordberg A (2015) Early astrocytosis in autosomal dominant Alzheimer’s disease measured in vivo by multi-tracer positron emission tomography. Sci Rep 5:16404. https://doi.org/10.1038/srep16404

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Rodriguez-Vieitez E, Saint-Aubert L, Carter SF, Almkvist O, Farid K, Scholl M, Chiotis K, Thordardottir S, Graff C, Wall A, Langstrom B, Nordberg A (2016) Diverging longitudinal changes in astrocytosis and amyloid PET in autosomal dominant Alzheimer’s disease. Brain 139(Pt 3):922–936. https://doi.org/10.1093/brain/awv404

    Article  PubMed  PubMed Central  Google Scholar 

  54. Rodriguez-Vieitez E, Ni R, Gulyas B, Toth M, Haggkvist J, Halldin C, Voytenko L, Marutle A, Nordberg A (2015) Astrocytosis precedes amyloid plaque deposition in Alzheimer APPswe transgenic mouse brain: a correlative positron emission tomography and in vitro imaging study. Eur J Nucl Med Mol Imaging 42(7):1119–1132. https://doi.org/10.1007/s00259-015-3047-0

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  55. Schott JM, Fox NC (2016) Inflammatory changes in very early Alzheimer’s disease: friend, foe, or don’t know? Brain 139(Pt 3):647–650. https://doi.org/10.1093/brain/awv405

    Article  PubMed  PubMed Central  Google Scholar 

  56. Acton PD, Friston KJ (1998) Statistical parametric mapping in functional neuroimaging: beyond PET and fMRI activation studies. Eur J Nucl Med 25(7):663–667

    PubMed  CAS  Google Scholar 

  57. Friston KJ (1995) Commentary and opinion: II. Statistical parametric mapping: ontology and current issues. J Cereb Blood Flow Metab 15(3):361–370. https://doi.org/10.1038/jcbfm.1995.45

    Article  PubMed  CAS  Google Scholar 

  58. Kiebel SJ, Ashburner J, Poline JB, Friston KJ (1997) MRI and PET coregistration—a cross validation of statistical parametric mapping and automated image registration. NeuroImage 5(4 Pt 1):271–279. https://doi.org/10.1006/nimg.1997.0265

    Article  PubMed  CAS  Google Scholar 

  59. Casanova R, Srikanth R, Baer A, Laurienti PJ, Burdette JH, Hayasaka S, Flowers L, Wood F, Maldjian JA (2007) Biological parametric mapping: a statistical toolbox for multimodality brain image analysis. NeuroImage 34(1):137–143. https://doi.org/10.1016/j.neuroimage.2006.09.011

    Article  PubMed  Google Scholar 

  60. Farid K, Carter SF, Rodriguez-Vieitez E, Almkvist O, Andersen P, Wall A, Blennow K, Portelius E, Zetterberg H, Nordberg A (2015) Case report of complex amyotrophic lateral sclerosis with cognitive impairment and cortical amyloid deposition. J Alzheimers Dis 47(3):661–667. https://doi.org/10.3233/JAD-141965

    Article  PubMed  Google Scholar 

  61. Patlak CS, Blasberg RG (1985) Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. Generalizations. J Cereb Blood Flow Metab 5(4):584–590. https://doi.org/10.1038/jcbfm.1985.87

    Article  PubMed  CAS  Google Scholar 

  62. Bergstrom M, Kumlien E, Lilja A, Tyrefors N, Westerberg G, Langstrom B (1998) Temporal lobe epilepsy visualized with PET with 11C-L-deuterium-deprenyl—analysis of kinetic data. Acta Neurol Scand 98(4):224–231

    Article  CAS  PubMed  Google Scholar 

  63. Petersen RC (2004) Mild cognitive impairment as a diagnostic entity. J Intern Med 256(3):183–194. https://doi.org/10.1111/j.1365-2796.2004.01388.x

    Article  PubMed  CAS  Google Scholar 

  64. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM (1984) 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(7):939–944

    Article  CAS  PubMed  Google Scholar 

  65. Nordberg A, Carter SF, Rinne J, Drzezga A, Brooks DJ, Vandenberghe R, Perani D, Forsberg A, Langstrom B, Scheinin N, Karrasch M, Nagren K, Grimmer T, Miederer I, Edison P, Okello A, Van Laere K, Nelissen N, Vandenbulcke M, Garibotto V, Almkvist O, Kalbe E, Hinz R, Herholz K (2013) A European multicentre PET study of fibrillar amyloid in Alzheimer’s disease. Eur J Nucl Med Mol Imaging 40(1):104–114. https://doi.org/10.1007/s00259-012-2237-2

    Article  PubMed  CAS  Google Scholar 

  66. Klunk WE, Engler H, Nordberg A, Wang Y, Blomqvist G, Holt DP, Bergstrom M, Savitcheva I, Huang GF, Estrada S, Ausen B, Debnath ML, Barletta J, Price JC, Sandell J, Lopresti BJ, Wall A, Koivisto P, Antoni G, Mathis CA, Langstrom B (2004) Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann Neurol 55(3):306–319. https://doi.org/10.1002/ana.20009

    Article  CAS  PubMed  Google Scholar 

  67. Mathis CA, Wang Y, Holt DP, Huang GF, Debnath ML, Klunk WE (2003) Synthesis and evaluation of 11C-labeled 6-substituted 2-arylbenzothiazoles as amyloid imaging agents. J Med Chem 46(13):2740–2754. https://doi.org/10.1021/jm030026b

    Article  PubMed  CAS  Google Scholar 

  68. Ashburner J, Friston KJ (2005) Unified segmentation. NeuroImage 26(3):839–851. https://doi.org/10.1016/j.neuroimage.2005.02.018

    Article  PubMed  Google Scholar 

  69. Hammers A, Allom R, Koepp MJ, Free SL, Myers R, Lemieux L, Mitchell TN, Brooks DJ, Duncan JS (2003) Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe. Hum Brain Mapp 19(4):224–247. https://doi.org/10.1002/hbm.10123

    Article  PubMed  PubMed Central  Google Scholar 

  70. Minoshima S, Frey KA, Foster NL, Kuhl DE (1995) Preserved pontine glucose metabolism in Alzheimer disease: a reference region for functional brain image (PET) analysis. J Comput Assist Tomogr 19(4):541–547

    Article  CAS  PubMed  Google Scholar 

  71. Lippa CF, Saunders AM, Smith TW, Swearer JM, Drachman DA, Ghetti B, Nee L, Pulaski-Salo D, Dickson D, Robitaille Y, Bergeron C, Crain B, Benson MD, Farlow M, Hyman BT, George-Hyslop SP, Roses AD, Pollen DA (1996) Familial and sporadic Alzheimer’s disease: neuropathology cannot exclude a final common pathway. Neurology 46(2):406–412

    Article  CAS  PubMed  Google Scholar 

  72. Benjamini Y, Hochberg Y. (1995) Controlling the false discovery rate—a practical and powerful approach to multiple testing. J Roy Stat Soc B Met 57:289–300

    Google Scholar 

  73. Turkheimer FE, Smith CB, Schmidt K (2001) Estimation of the number of “true” null hypotheses in multivariate analysis of neuroimaging data. NeuroImage 13(5):920–930. https://doi.org/10.1006/nimg.2001.0764

    Article  PubMed  CAS  Google Scholar 

  74. Edison P, Hinz R, Ramlackhansingh A, Thomas J, Gelosa G, Archer HA, Turkheimer FE, Brooks DJ (2012) Can target-to-pons ratio be used as a reliable method for the analysis of [11C]PIB brain scans? NeuroImage 60(3):1716–1723. https://doi.org/10.1016/j.neuroimage.2012.01.099

    Article  PubMed  CAS  Google Scholar 

  75. Herholz K (2010) Cerebral glucose metabolism in preclinical and prodromal Alzheimer’s disease. Expert Rev. Neurother 10(11):1667–1673. https://doi.org/10.1586/ern.10.136

    Article  PubMed  CAS  Google Scholar 

  76. Lopresti BJ, Klunk WE, Mathis CA, Hoge JA, Ziolko SK, Lu X, Meltzer CC, Schimmel K, Tsopelas ND, DeKosky ST, Price JC (2005) Simplified quantification of Pittsburgh compound B amyloid imaging PET studies: a comparative analysis. J Nucl Med 46(12):1959–1972

    PubMed  CAS  Google Scholar 

Download references

Acknowledgements

We are grateful to the staff at the Uppsala PET Centre. This work was financially supported by grants from the Swedish Research Council (project 05817), the Swedish Foundation for Strategic Research (SSF), the Strategic Research Programme in Neuroscience at Karolinska Institutet, Neuroscience program, the Stockholm County Council-Karolinska Institutet regional agreement on medical training and clinical research (ALF grant), the Swedish Brain Foundation, the Swedish Alzheimer Foundation (Alzheimerfonden), Demensfonden, the EU FP7 large-scale integrating project INMiND (http://www.uni-muenster.de/INMiND), the Foundation for Old Servants, Karolinska Institutet’s Foundation for Aging Research, Gun and Bertil Stohne’s Foundation, Loo and Hans Osterman’s Foundation, and Åke Wiberg’s Foundation.

Author information

Authors and Affiliations

  1. Division of Translational Alzheimer Neurobiology, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden

    Elena Rodriguez-Vieitez & Agneta Nordberg

  2. Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden

    Agneta Nordberg

Authors
  1. Elena Rodriguez-Vieitez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Agneta Nordberg
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Elena Rodriguez-Vieitez .

Editor information

Editors and Affiliations

  1. Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany

    Robert Perneczky

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Rodriguez-Vieitez, E., Nordberg, A. (2018). Imaging Neuroinflammation: Quantification of Astrocytosis in a Multitracer PET Approach. In: Perneczky, R. (eds) Biomarkers for Alzheimer’s Disease Drug Development. Methods in Molecular Biology, vol 1750. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7704-8_16

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-7704-8_16

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7703-1

  • Online ISBN: 978-1-4939-7704-8

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation