Clinical and Translational Imaging

, Volume 3, Issue 6, pp 403–416 | Cite as

Challenges of quantification of TSPO in the human brain

  • Rainer Hinz
  • Ronald Boellaard
Review Article


The first positron emission tomography (PET) imaging studies in humans of the translocator protein 18 kDa (TSPO) were conducted in the 1980s with a primary interest in quantifying the binding in peripheral organs such as the heart, spleen and kidneys to what was then known as the peripheral benzodiazepine receptor. However, the number of studies rapidly increased when the focus of the research shifted to the brain, and [11C](R)-PK11195 became de facto the reference radiotracer for all in vivo TSPO binding assays. For the quantitative analysis of the data which initially was performed with compartmental models and plasma input functions, this led to the adoption of the reference tissue kinetic models which were developed at the same time in the mid 1990s. In contrast to many neuro-receptor studies of the dopaminergic or serotonergic system, it was not possible to anatomically define a brain region devoid of TSPO that could serve as a reference region. Instead, data-driven techniques were adopted that extracted at the voxel level reference tissue kinetics without incorporating anatomical information. In this review, an overview of the development, use and challenges of the various quantitative analysis methods for TSPO brain PET data is given. The different approaches to (automatically) extract reference tissue input curves from the dynamic images are discussed. Descriptions of key PET imaging studies exploring TSPO binding quantitatively in disease populations are included.


Positron emission tomography (PET) Quantification [11C]PK11195 Translocator protein 18 kDa (TSPO) 



Alzheimer’s disease


Density of sites available to bind radioligand in vivo


Blood–brain barrier


Blood flow


Binding potential


Binding potential relative to the free ligand concentration in plasma


Binding potential relative to the non-displaceable binding in tissue


Cerebral blood flow


Central nervous system


Computed tomography


High-affinity binder


Huntington’s disease


High-performance liquid chromatography


High Resolution Research Tomograph


Imaging of neuroinflammation in neurodegenerative diseases


Dissociation constant


Low-affinity binder


Mixed affinity binder


Mild cognitive impairment


Magnetic resonance imaging


Positron emission tomography




Partial volume effect


Region of interest


Standard deviation


Solid-phase extraction


Simplified reference tissue model


Simplified reference tissue model with vascular component


Standard uptake value


Supervised cluster analysis with four kinetic classes


Supervised cluster analysis with six kinetic classes


Time–activity curve


Thin-layer chromatography


Translocator protein 18 kDa


Non-displaceable volume of distribution


Total volume of distribution



We gratefully acknowledge Christian Prenant and Gavin D. Brown for their explanations provided on the radiochemistry, David J. Brooks for the invitation to Århus and the stimulating discussions on [11C](R)-PK11195 data analysis there, Federico Roncaroli for his advice on neuropathological data and the European Union’s Seventh Framework Programme (FP7/2007-2013) for financial support under the Grant agreement HEALTH-F2-2011-278850 (Imaging of Neuroinflammation in Neurodegenerative Diseases) bringing the INMiND consortium together.

Authors’ contributions

R Hinz: Design and content planning of the article; literature search and review; manuscript writing, formatting and editing; correspondence with the editorial office. R Boellaard: Design and content planning of the article; literature search and review; manuscript writing and editing; data processing for the preparation of the figures.

Compliance with ethical standards

Conflict of interest

The authors declare no conflicts of interest.

Ethical approval and informed consent

All procedures performed in studies, with human participants, in which the authors were involved, were conducted in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in those studies.

Human rights and animal standards

This review article does not contain studies with animals performed by any of the authors.


  1. 1.
    Charbonneau P, Syrota A, Crouzel C, Valois JM, Prenant C, Crouzel M (1986) Peripheral-type benzodiazepine receptors in the living heart characterized by positron emission tomography. Circulation 73:476–483. doi: 10.1161/01.CIR.73.3.476 CrossRefPubMedGoogle Scholar
  2. 2.
    Bergström M, Mosskin M, Ericson K, Ehrin E, Thorell JO, von Holst H, Norén G, Persson A, Halldin C, Stone-Elander S (1986) Peripheral benzodiazepine binding sites in human gliomas evaluated with positron emission tomography. Acta Radiol Suppl 369:409–411PubMedGoogle Scholar
  3. 3.
    Junck L, Olson JM, Ciliax BJ, Koeppe RA, Watkins GL, Jewett DM, McKeever PE, Wieland DM, Kilbourn MR, Starosta-Rubinstein S, Mancini WR, Kuhl DE, Greenberg HS, Young AB (1989) PET imaging of human gliomas with ligands for the peripheral benzodiazepine binding site. Ann Neurol 26:752–758. doi: 10.1002/ana.410260611 CrossRefPubMedGoogle Scholar
  4. 4.
    Ramsay SC, Weiller C, Myers R, Cremer JE, Luthra SK, Lammertsma AA, Frackowiak RS (1992) Monitoring by PET of macrophage accumulation in brain after ischaemic stroke. Lancet 339:1054–1055. doi: 10.1016/0140-6736(92)90576-O CrossRefPubMedGoogle Scholar
  5. 5.
    Blomqvist G, Pauli S, Farde L, Eriksson L, Persson A, Halldin C (1989) Dynamic models of reversible ligand binding. In: Beckers C, Goffinet A, Bol A (eds) Positron emission tomography in clinical research and clinical diagnosis: tracer modelling and radioreceptors. Kluwer Academic Publishers, Dardrecht, pp 35–44. ISBN 0-7923-0254-0Google Scholar
  6. 6.
    Cunningham VJ, Hume SP, Price GR, Ahier RG, Cremer JE, Jones AKP (1991) Compartmental analysis of diprenorphine binding to opiate receptors in the rat in vivo and its comparison with equilibrium data in vitro. J Cereb Blood Flow Metab 11:1–9. doi: 10.1038/jcbfm.1991.1 CrossRefPubMedGoogle Scholar
  7. 7.
    Lammertsma AA, Bench CJ, Hume SP, Osman S, Gunn K, Brooks DJ, Frackowiak RSJ (1996) Comparison of methods for analysis of clinical [11C] raclopride studies. J Cereb Blood Flow Metab 16:42–52. doi: 10.1097/00004647-199601000-00005 CrossRefPubMedGoogle Scholar
  8. 8.
    Lammertsma AA, Hume SP (1996) Simplified reference tissue model for PET receptor studies. Neuroimage 4:153–158. doi: 10.1006/nimg.1996.0066 CrossRefPubMedGoogle Scholar
  9. 9.
    Logan J, Fowler JS, Volkow ND, Wang G-J, Ding YS, Alexoff DL (1996) Distribution volume ratios without blood sampling from graphical analysis of PET data. J Cereb Blood Flow Metab 16:834–840. doi: 10.1097/00004647-199609000-00008 CrossRefPubMedGoogle Scholar
  10. 10.
    Pike VW, Halldin C, Crouzel C, Barre L, Nutt DJ, Osman S, Shah F, Turton DR, Waters SL (1993) Radioligands for PET studies of central benzodiazepine receptors and PK (peripheral benzodiazepine) binding sites—current status. Nucl Med Biol 20:503–525. doi: 10.1016/0969-8051(93)90082-6 CrossRefPubMedGoogle Scholar
  11. 11.
    De Vos F, Dumont F, Santens P, Slegers G, Dierckx R, De Reuck J (1999) High-performance liquid chromatographic determination of [11C]1-(2-chlorophenyl)-N-methyl-N-(1-methylpropyl)-3-isoquinoline carboxamide in mouse plasma and tissue and in human plasma. J Chromatogr B Biomed Sci Appl 736:61–66CrossRefPubMedGoogle Scholar
  12. 12.
    Greuter HNJM, van Ophemert PLB, Luurtsema G, van Berckel BNM, Franssen EJF, Windhorst BD, Lammertsma AA (2005) Optimizing an online SPE–HPLC method for analysis of (R)-[11C]1-(2-chlorophenyl)-N-methyl-N-(1-methylpropyl)-3-isoquinolinecarboxamide [(R)-[11C]PK11195] and its metabolites in humans. Nucl Med Biol 32:307–312. doi: 10.1016/j.nucmedbio.2004.12.005 CrossRefPubMedGoogle Scholar
  13. 13.
    Shah F, Hume SP, Pike VW, Ashworth S, McDermott J (1994) Synthesis of the enantiomers of [N-methyl-11C]PK 11195 and comparison of their behaviours as radioligands for PK binding sites in rats. Nucl Med Biol 21:573–581. doi: 10.1016/0969-8051(94)90022-1 CrossRefPubMedGoogle Scholar
  14. 14.
    Jaremko Ł, Jaremko M, Giller K, Becker S, Zweckstetter M (2014) Structure of the mitochondrial translocator protein in complex with a diagnostic ligand. Science 343:1363–1366. doi: 10.1126/science.1248725 CrossRefPubMedGoogle Scholar
  15. 15.
    Roivainen A, Någren K, Hirvonen J, Oikonen V, Virsu P, Tolvanen T, Rinne JO (2009) Whole-body distribution and metabolism of [N-methyl-11C](R)-1-(2-chlorophenyl)-N-(1-methylpropyl)-3-isoquinolinecarboxamide in humans; an imaging agent for in vivo assessment of peripheral benzodiazepine receptor activity with positron emission tomography. Eur J Nucl Med Mol Imaging 36:671–682. doi: 10.1007/s00259-008-1000-1 CrossRefPubMedGoogle Scholar
  16. 16.
    Jučaite A, Cselényi Z, Arvidsson A, Åhlberg G, Julin P, Varnäs K, Stenkrona P, Andersson J, Halldin C, Farde L (2012) Kinetic analysis and test-retest variability of the radioligand [11C](R)-PK11195 binding to TSPO in the human brain—a PET study in control subjects. EJNMMI Res 2:15. doi: 10.1186/2191-219X-2-15 CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Lamare F, Hinz R, Gaemperli O, Pugliese F, Mason JC, Spinks TJ, Camici PG, Rimoldi OE (2011) Detection and quantification of large vessel inflammation with 11C-(R)-PK11195 PET/CT. J Nucl Med 52:33–39. doi: 10.2967/jnumed.110.079038 CrossRefPubMedGoogle Scholar
  18. 18.
    Groom GN, Junck L, Foster NL, Frey KA, Kuhl DE (1995) PET of peripheral benzodiazepine binding sites in the microgliosis of Alzheimer’s disease. J Nucl Med 36:2207–2210PubMedGoogle Scholar
  19. 19.
    Rozemuller JM, van der Valk P, Eikelenboom P (1992) Activated microglia and cerebral amyloid deposits in Alzheimer’s disease. Res Immunol 143:646–649. doi: 10.1016/0923-2494(92)80050-U CrossRefPubMedGoogle Scholar
  20. 20.
    Wyss-Coray T (2006) Inflammation in Alzheimer disease: driving force, bystander or beneficial response? Nat Med 12:1005–1015. doi: 10.1038/nm1484 PubMedGoogle Scholar
  21. 21.
    Doble A, Malgouris C, Daniel M, Daniel N, Imbault F, Basbaum A, Uzan A, Gueremy C, Le Fur G (1987) Labelling of peripheral-type benzodiazepine binding sites in human brain with [3H]PK 11195: anatomical and subcellular distribution. Brain Res Bull 18:49–61. doi: 10.1016/0361-9230(87)90033-5 CrossRefPubMedGoogle Scholar
  22. 22.
    Owen DR, Guo Q, Kalk NJ, Colasanti A, Kalogiannopoulou D, Dimber R, Lewis YL, Libri V, Barletta J, Ramada-Magalhaes J, Kamalakaran A, Nutt DJ, Passchier J, Matthews PM, Gunn RN, Rabiner EA (2014) Determination of [11C]PBR28 binding potential in vivo: a first human TSPO blocking study. J Cereb Blood Flow Metab 34:989–994. doi: 10.1038/jcbfm.2014.46 CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Owen DR, Yeo AJ, Gunn RN, Song K, Wadsworth G, Lewis A, Rhodes C, Pulford DJ, Bennacef I, Parker CA, StJean PL, Cardon LR, Mooser VE, Matthews PM, Rabiner EA, Rubio JP (2012) An 18-kDa translocator protein (TSPO) polymorphism explains differences in binding affinity of the PET radioligand PBR28. J Cereb Blood Flow Metab 32:1–5. doi: 10.1038/jcbfm.2011.147 CrossRefPubMedGoogle Scholar
  24. 24.
    Lassen NA, Bartenstein PA, Lammertsma AA, Prevett MC, Turton DR, Luthra SK, Osman S, Bloomfield PM, Jones T, Patsalos PN, O’Connell MT, Duncan JS, Vanggaard Andersen J (1995) Benzodiazepine receptor quantification in vivo in humans using [11C] flumazenil and PET: application of the steady-state principle. J Cereb Blood Flow Metab 15:152–165. doi: 10.1038/jcbfm.1995.17 CrossRefPubMedGoogle Scholar
  25. 25.
    Cunningham VJ, Rabiner EA, Slifstein M, Laruelle M, Gunn RN (2010) Measuring drug occupancy in the absence of a reference region: the Lassen plot re-visited. J Cereb Blood Flow Metab 30:46–50. doi: 10.1038/jcbfm.2009.190-&gt CrossRefPubMedGoogle Scholar
  26. 26.
    Mintun MA, Raichle ME, Kilbourn MR, Wooten GF, Welch MJ (1984) A quantitative model for the in vivo assessment of drug binding sites with positron emission tomography. Ann Neurol 15:217–227. doi: 10.1002/ana.410150302 CrossRefPubMedGoogle Scholar
  27. 27.
    Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, Holden J, Houle S, Huang S-C, Ichise M, Iida H, Ito H, Kimura Y, Koeppe RA, Knudsen GM, Knuuti J, Lammertsma AA, Laruelle M, Logan J, Maguire RP, Mintun MA, Morris ED, Parsey R, Price JC, Slifstein M, Sossi V, Suhara T, Votaw JR, Wong DF, Carson RE (2007) Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab 27:1533–1539. doi: 10.1038/sj.jcbfm.9600493 CrossRefPubMedGoogle Scholar
  28. 28.
    Koeppe RA, Holthoff VA, Frey KA, Kilbourn MR, Kuhl DE (1991) Compartmental analysis of [11C] flumazenil kinetics for the estimation of ligand receptor distribution using positron emission tomography. J Cereb Blood Flow Metab 11:735–744. doi: 10.1038/jcbfm.1991.130 CrossRefPubMedGoogle Scholar
  29. 29.
    Carson RE, Channing MA, Blasberg RG, Dunn BB, Cohen RM, Rice KC, Herscovitch P (1993) Comparison of bolus and infusion methods for receptor quantitation: application to [18F]cyclofoxy and positron emission tomography. J Cereb Blood Flow Metab 13:24–42. doi: 10.1038/jcbfm.1993.6 CrossRefPubMedGoogle Scholar
  30. 30.
    Friedlander G, Kennedy JW, Macias ES, Miller JM (1981) Chapter 5 Equations of radioactive decay and growth. In: Nuclear and radiochemistry, 3rd edn. Wiley, New York, pp 191–205Google Scholar
  31. 31.
    Slifstein M (2008) Revisiting an old issue: the discrepancy between tissue ratio-derived binding parameters and kinetic modeling-derived parameters after a bolus of the serotonin transporter radioligand 123I-ADAM. J Nucl Med 49:176–178. doi: 10.2967/jnumed.107.046631 CrossRefPubMedGoogle Scholar
  32. 32.
    Slifstein M, Laruelle M (2001) Models and methods for derivation of in vivo neuroreceptor parameters with PET and SPECT reversible radiotracers. Nucl Med Biol 28:595–608. doi: 10.1016/S0969-8051(01)00214-1 CrossRefPubMedGoogle Scholar
  33. 33.
    Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144:646–674. doi: 10.1016/j.cell.2011.02.013 CrossRefPubMedGoogle Scholar
  34. 34.
    Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100:57–70. doi: 10.1016/S0092-8674(00)81683-9 CrossRefPubMedGoogle Scholar
  35. 35.
    Cagnin A, Brooks DJ, Kennedy AM, Gunn RN, Myers R, Turkheimer FE, Jones T, Banati RB (2001) In-vivo measurement of activated microglia in dementia. Lancet 358:461–467. doi: 10.1016/S0140-6736(01)05625-2 CrossRefPubMedGoogle Scholar
  36. 36.
    Gunn RN, Lammertsma AA, Hume SP, Cunningham VJ (1997) Parametric imaging of ligand-receptor binding in PET using a simplified reference region model. Neuromage 6:279–287. doi: 10.1006/nimg.1997.0303 CrossRefGoogle Scholar
  37. 37.
    Herholz K, Patlak CS (1987) The influence of tissue heterogeneity on results of fitting nonlinear model equations to regional tracer uptake curves: with an application to compartmental models used in positron emission tomography. J Cereb Blood Flow Metab 7:214–229. doi: 10.1038/jcbfm.1987.47 CrossRefPubMedGoogle Scholar
  38. 38.
    Mahalanobis PC (1936) On the generalised distance in statistics. Proc Natl Inst Sci India 12:49–55Google Scholar
  39. 39.
    Rousseeuw PJ (1987) Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math 20:53–65. doi: 10.1016/0377-0427(87)90125-7 CrossRefGoogle Scholar
  40. 40.
    O’Sullivan F (1993) Imaging radiotracer model parameters in PET: a mixture analysis approach. IEEE Trans Med Imaging 12:399–412. doi: 10.1109/42.241867 CrossRefPubMedGoogle Scholar
  41. 41.
    Ashburner J, Haslam J, Taylor C, Cunningham VJ, Jones T (1996) A cluster analysis approach for the characterization of dynamic PET data. In: Myers R, Cunningham V, Bailey D, Jones T (eds) Quantification of brain function using PET. Academic Press, San Diego, pp 301–306. doi: 10.1016/B978-012389760-2/50061-X. ISBN 0-12-389760-2CrossRefGoogle Scholar
  42. 42.
    Myers R, Gunn RN, Cunningham VJ, Banati RB, Jones T (1999) Cluster analysis and the reference tissue model in the analysis of clinical [11C]PK11195 PET. J Cereb Blood Flow Metab 19:S789Google Scholar
  43. 43.
    Cagnin A, Myers R, Gunn RN, Turkheimer FE, Cunningham VJ, Brooks DJ, Jones T, Banati RB (2000) Imaging activated microglia in the aging human brain. In: Gjedde A, Hansen SB, Knudsen GM, Paulson OB (eds) Physiological imaging of the brain with PET. Academic Press, San Diego, pp 361–367. ISBN 0-12-285751-8Google Scholar
  44. 44.
    Banati RB, Newcombe J, Gunn RN, Cagnin A, Turkheimer F, Heppner F, Price G, Wegner F, Giovannoni G, Miller DH, Perkin GD, Smith T, Hewson AK, Bydder G, Kreutzberg GW, Jones T, Cuzner ML, Myers R (2000) The peripheral benzodiazepine binding site in the brain in multiple sclerosis: quantitative in vivo imaging of microglia as a measure of disease activity. Brain 123:2321–2337. doi: 10.1093/brain/123.11.2321 CrossRefPubMedGoogle Scholar
  45. 45.
    Kropholler MA, Boellaard R, van Berckel BN, Schuitemaker A, Kloet RW, Lubberink MJ, Jonker C, Scheltens P, Lammertsma AA (2007) Evaluation of reference regions for (R)-[11C]PK11195 studies in Alzheimer’s disease and mild cognitive impairment. J Cereb Blood Flow Metab 27:1965–1974. doi: 10.1038/sj.jcbfm.9600488 CrossRefPubMedGoogle Scholar
  46. 46.
    Turkheimer FE, Edison P, Pavese N, Roncaroli F, Anderson AN, Hammers A, Gerhard A, Hinz R, Tai YF, Brooks DJ (2007) Reference and target region modeling of [11C]-(R)-PK11195 brain studies. J Nucl Med 48:158–167PubMedGoogle Scholar
  47. 47.
    Chen J, Gunn S, Nixon M, Myers R, Gunn R (2000) A supervised method for PET reference region extraction. In: Arridge S, Todd-Pokropek A (eds) Medical image understanding and analysis MIUA 2000: proceedings of the fourth annual conference. University College London, UK, pp 179–182. ISBN 1-901725-11-1Google Scholar
  48. 48.
    Lawson CL, Hanson RJ (1995) Solving least squares problems. Society for Industrial and Applied Mathematics (SIAM), Philadelphia. ISBN 0-89871-356-0Google Scholar
  49. 49.
    Cunningham VJ, Jones T (1993) Spectral analysis of dynamic PET studies. J Cereb Blood Flow Metab 13:15–23. doi: 10.1038/jcbfm.1993.5 CrossRefPubMedGoogle Scholar
  50. 50.
    Hinz R, Jones M, Bloomfield PM, Boellaard R, Turkheimer FE, Tyrrell PJ (2008) Reference tissue kinetics extraction from [11C]-(R)-PK11195 scans on the High Resolution Research Tomograph (HRRT). Neuroimage 41(suppl. 2):T65. doi: 10.1016/j.neuroimage.2008.04.035 CrossRefGoogle Scholar
  51. 51.
    Drake C, Boutin H, Jones MS, Denes A, McColl BW, Selvarajah JR, Hulme S, Georgiou RF, Hinz R, Gerhard A, Vail A, Prenant C, Julyan P, Maroy R, Brown G, Smigova A, Herholz K, Kassiou M, Crossman D, Francis S, Proctor SD, Russell JC, Hopkins SJ, Tyrrell PJ, Rothwell NJ, Allan SM (2011) Brain inflammation is induced by co-morbidities and risk factors for stroke. Brain Behav Immun 25:1113–1122. doi: 10.1016/j.bbi.2011.02.008 CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Boellaard R, Turkheimer FE, Hinz R, Schuitemaker A, Scheltens P, van Berckel BNM, Lammertsma AA (2008) Performance of a modified supervised cluster algorithm for extracting reference region input functions from (R)-[11C]PK11195 brain PET studies. In: IEEE Nuclear Sciece Symposium Conference Record, NSS ′08, Dresden, pp 5400–5402Google Scholar
  53. 53.
    Folkersma H, Boellaard R, Vandertop WP, Kloet RW, Lubberink M, Lammertsma AA, van Berckel BNM (2009) Reference tissue models and blood–brain barrier disruption: lessons from (R)-[11C]PK11195 in traumatic brain injury. J Nucl Med 50:1975–1979. doi: 10.2967/jnumed.109.067512 CrossRefPubMedGoogle Scholar
  54. 54.
    Costes N, Blanc C, Bouillot C, Yankam Njiwa J, Bolbos R, Bouvard S, Chauveau F, Le Bars D, Turkheimer FE, Hammers A (2013) Supervised clustering for determining a reference region for [11C]PK11195 PET: adaptation to rat PET studies. In: 11th international conference on quantification of brain function with PET (BrainPET’13), Shanghai, China, 20–23 May 2013Google Scholar
  55. 55.
    Su Z, Herholz K, Gerhard A, Roncaroli F, Du Plessis D, Jackson A, Turkheimer F, Hinz R (2013) [11C]-(R)PK11195 tracer kinetics in the brain of glioma patients and a comparison of two referencing approaches. Eur J Nucl Med Mol Imaging 40:1406–1419. doi: 10.1007/s00259-013-2447-2 CrossRefPubMedPubMedCentralGoogle Scholar
  56. 56.
    Holland GP, Hunter JA, Su Z, Kobylecki C, Gerhard A, Hinz R (2014) Extraction of reference tissue kinetics from [11C]-(R)PK11195 brain scans: limits of applications. In: 10th international symposium on functional neuroreceptor mapping (NRM) of the living brain, Egmond aan Zee, the Netherlands, 21–24 May 2014. Abstract Book, 117.
  57. 57.
    Yaqub M, van Berckel BN, Schuitemaker A, Hinz R, Turkheimer FE, Tomasi G, Lammertsma AA, Boellaard R (2012) Optimization of supervised cluster analysis for extracting reference tissue input curves in (R)-[11C]PK11195 brain PET studies. J Cereb Blood Flow Metab 32:1600–1608. doi: 10.1038/jcbfm.2012.59 CrossRefPubMedPubMedCentralGoogle Scholar
  58. 58.
    Kropholler MA, Boellaard R, Schuitemaker A, van Berckel BN, Luurtsema G, Windhorst AD, Lammertsma AA (2005) Development of a tracer kinetic plasma input model for (R)-[11C]PK11195 brain studies. J Cereb Blood Flow Metab 25:842–851. doi: 10.1038/sj.jcbfm.9600092 CrossRefPubMedGoogle Scholar
  59. 59.
    Kropholler MA, Boellaard R, Schuitemaker A, Folkersma H, van Berckel BN, Lammertsma AA (2006) Evaluation of reference tissue models for the analysis of [11C](R)-PK11195 studies. J Cereb Blood Flow Metab 26:1431–1441. doi: 10.1038/sj.jcbfm.9600289 CrossRefPubMedGoogle Scholar
  60. 60.
    Tomasi G, Edison P, Bertoldo A, Roncaroli F, Singh P, Gerhard A, Cobelli C, Brooks DJ, Turkheimer FE (2008) Novel reference region model reveals increased microglial and reduced vascular binding of 11C-(R)-PK11195 in patients with Alzheimer’s disease. J Nucl Med 49:1249–1256. doi: 10.2967/jnumed.108.050583 CrossRefPubMedGoogle Scholar
  61. 61.
    Gunn RN, Sargent PA, Bench CJ, Rabiner EA, Osman S, Pike VW, Hume SP, Grasby PM, Lammertsma AA Tracer kinetic modeling of the 5-HT1A receptor ligand [carbonyl-11C]WAY- 100635 for PET. Neuroimage 8: 426–440. doi:  10.1006/nimg.1998.0379
  62. 62.
    Rizzo G, Veronese M, Tonietto M, Zanotti-Fregonara P, Turkheimer FE, Bertoldo A (2014) Kinetic modeling without accounting for the vascular component impairs the quantification of [11C]PBR28 brain PET data. J Cereb Blood Flow Metab 34:1060–1069. doi: 10.1038/jcbfm.2014.55 CrossRefPubMedPubMedCentralGoogle Scholar
  63. 63.
    Ouchi Y, Yoshikawa E, Sekine Y, Futatsubashi M, Kanno T, Ogusu T, Torizuka T (2005) Microglial activation and dopamine terminal loss in early Parkinson’s disease. Ann Neurol 57:168–175. doi: 10.1002/ana.20338 CrossRefPubMedGoogle Scholar
  64. 64.
    Schuitemaker A, van der Doef TF, Boellaard R, van der Flier WM, Yaqub M, Windhorst AD, Barkhof F, Jonker C, Kloet RW, Lammertsma AA, Scheltens P, van Berckel BN (2012) Microglial activation in healthy aging. Neurobiol Aging 33:1067–1072. doi: 10.1016/j.neurobiolaging.2010.09.016 CrossRefPubMedGoogle Scholar
  65. 65.
    Kumar A, Muzik O, Shandal V, Chugani D, Chakraborty P, Chugani HT (2012) Evaluation of age-related changes in translocator protein (TSPO) in human brain using 11C-[R]-PK11195 PET. J Neuroinflammation 9:232. doi: 10.1186/1742-2094-9-232 CrossRefPubMedPubMedCentralGoogle Scholar
  66. 66.
    Gulyás B, Vas A, Tóth M, Takano A, Varrone A, Cselényi Z, Schain M, Mattsson P, Halldin C (2011) Age and disease related changes in the translocator protein (TSPO) system in the human brain: positron emission tomography measurements with [11C]vinpocetine. Neuroimage 56:1111–1121. doi: 10.1016/j.neuroimage.2011.02.020 CrossRefPubMedGoogle Scholar
  67. 67.
    Suridjan I, Rusjan PM, Voineskos AN, Selvanathan T, Setiawan E, Strafella AP, Wilson AA, Meyer JH, Houle S, Mizrahi R (2014) Neuroinflammation in healthy aging: a PET study using a novel translocator protein 18 kDa (TSPO) radioligand, [18F]-FEPPA. Neuroimage 84:868–875. doi: 10.1016/j.neuroimage.2013.09.021 CrossRefPubMedGoogle Scholar
  68. 68.
    Schuitemaker A, Kropholler MA, Boellaard R, van der Flier WM, Kloet RW, van der Doef TF, Knol DL, Windhorst AD, Luurtsema G, Barkhof F, Jonker C, Lammertsma AA, Scheltens P, van Berckel BN (2013) Microglial activation in Alzheimer’s disease: an (R)-[11C]PK11195 positron emission tomography study. Neurobiol Aging 34:128–136. doi: 10.1016/j.neurobiolaging.2012.04.021 CrossRefPubMedGoogle Scholar
  69. 69.
    Hunter HJA, Hinz R, Gerhard A, Talbot PS, Su Z, Holland G, Hopkins SJ, Griffiths CEM, Kleyn CE (2015) Brain inflammation and psoriasis: a [11C]-(R)-PK11195 positron emission tomography study. Br J Dermatol. doi: 10.1111/bjd.13788 Google Scholar
  70. 70.
    Golla SSV, Boellaard R, Oikonen V, Hoffmann A, van Berckel BNM, Windhorst AD, Virta J, Haaparanta-Solin M, Luoto P, Savisto N, Solin O, Valencia R, Thiele A, Eriksson J, Schuit RC, Lammertsma AA, Rinne JO (2015) Quantification of [18F]DPA-714 binding in the human brain: initial studies in healthy controls and Alzheimer’s disease patients. J Cereb Blood Flow Metab 35:766–772. doi: 10.1038/jcbfm.2014.261 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Italian Association of Nuclear Medicine and Molecular Imaging 2015

Authors and Affiliations

  1. 1.Wolfson Molecular Imaging CentreUniversity of ManchesterManchesterUK
  2. 2.Department of Radiology and Nuclear MedicineVU University Medical CenterAmsterdamThe Netherlands

Personalised recommendations