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DOCK–PET: database of CNS kinetic parameters in the healthy human brain for existing PET tracers

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Abstract

Purpose

Information about developed positron emission tomography (PET) tracers and obtained clinical PET images is publicly available in a database. However, findings regarding the kinetic parameters of PET tracers are yet to be summarized. Therefore, in this study, we created an open-access database of central nervous system (CNS) kinetic parameters in the healthy human brain for existing PET tracers (DOCK–PET).

Methods

Our database includes information on the kinetic parameters and compounds of existing CNS–PET tracers. The kinetic parameter dataset comprises the analysis methods, VT, BPND, K parameters, relevant literature, and study details. The list of PET tracers and kinetic parameter information was compiled through keyword-based searches of PubMed and the Molecular Imaging and Contrast Agent Database (MICAD). The kinetic parameters obtained, including VT, BPND, and K parameters, were reorganized based on the defined brain anatomical regions. All data were rigorously double-checked before being summarized in Microsoft Excel and JavaScript Object Notation (JSON) formats.

Results

Of the 247 PET tracers identified through searches using the PubMed and MICAD websites, the kinetic parameters of 120 PET tracers were available. Among the 120 PET tracers, compound structures with chemical and physical properties were obtained from the PubChem website or the ChemDraw software. Furthermore, the affinity information of the 104 PET tracers was gathered from PubChem or extensive literature surveys of the 120 PET tracers.

Conclusions

We developed a comprehensive open-access database, DOCK–PET, that includes both kinetic parameters of healthy humans and compound information for existing CNS–PET tracers.

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References

  1. Phelps ME, Hoffman EJ, Mullani NA, Ter-Pogossian MM. Application of annihilation coincidence detection to transaxial reconstruction tomography. J Nucl Med. 1975;16(3):210–24.

    CAS  PubMed  Google Scholar 

  2. Ter-Pogossian MM, Phelps ME, Hoffman EJ, Mullani NA. A positron-emission transaxial tomograph for nuclear imaging (PETT). Radiology. 1975;114(1):89–98.

    Article  CAS  PubMed  Google Scholar 

  3. Ietswaart R, Arat S, Chen AX, Farahmand S, Kim B, DuMouchel W, et al. Machine learning guided association of adverse drug reactions with in vitro target-based pharmacology. EBioMedicine. 2020;57: 102837.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kundu I, Paul G, Banerjee R. A machine learning approach towards the prediction of protein-ligand binding affinity based on fundamental molecular properties. RSC Adv. 2018;8(22):12127–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Dang NL, Matlock MK, Hughes TB, Swamidass SJ. The metabolic rainbow: deep learning phase I metabolism in five colors. J Chem Inf Model. 2020;60(3):1146–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Suhara T, Chaki S, Kimura H, Furusawa M, Matsumoto M, Ogura H, et al. Strategies for utilizing neuroimaging biomarkers in CNS drug discovery and development: CINP/JSNP working group report. Int J Neuropsychopharmacol. 2017;20(4):285–94.

    CAS  PubMed  Google Scholar 

  7. Rahman M, Watabe H. Online molecular image repository and analysis system: a multicenter collaborative open-source infrastructure for molecular imaging research and application. Comput Biol Med. 2018;1(96):233–40.

    Article  Google Scholar 

  8. Gorgolewski KJ, Auer T, Calhoun VD, Craddock RC, Das S, Duff EP, et al. The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Sci Data. 2016;21(3): 160044.

    Article  Google Scholar 

  9. Norgaard M, Matheson GJ, Hansen HD, Thomas A, Searle G, Rizzo G, et al. PET-BIDS, an extension to the brain imaging data structure for positron emission tomography. Sci Data. 2022;9(1):65.

    Article  PubMed  PubMed Central  Google Scholar 

  10. McCluskey SP, Plisson C, Rabiner EA, Howes O. Advances in CNS PET: the state-of-the-art for new imaging targets for pathophysiology and drug development. Eur J Nucl Med Mol Imaging. 2020;47(2):451–89.

    Article  CAS  PubMed  Google Scholar 

  11. Guo Q, Brady M, Gunn RN. A biomathematical modeling approach to central nervous system radioligand discovery and development. J Nucl Med. 2009;50(10):1715–23.

    Article  CAS  PubMed  Google Scholar 

  12. Hammers A, Allom R, Koepp MJ, Free SL, Myers R, Lemieux L, et al. Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe. Hum Brain Mapp. 2003;19(4):224–47.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Watabe H, Ikoma Y, Kimura Y, Naganawa M, Shidahara M. PET kinetic analysis–compartmental model. Ann Nucl Med. 2006;20(9):583–8.

    Article  CAS  PubMed  Google Scholar 

  14. Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab. 2007;27(9):1533–9.

    Article  CAS  PubMed  Google Scholar 

  15. Kudo Y, Okamura N, Furumoto S, Tashiro M, Furukawa K, Maruyama M, et al. 2-(2-[2-Dimethylaminothiazol-5-yl]ethenyl)-6- (2-[fluoro]ethoxy)benzoxazole: a novel PET agent for in vivo detection of dense amyloid plaques in Alzheimer’s disease patients. J Nucl Med. 2007;48(4):553–61.

    Article  CAS  PubMed  Google Scholar 

  16. Ito H, Shinotoh H, Shimada H, Miyoshi M, Yanai K, Okamura N, et al. Imaging of amyloid deposition in human brain using positron emission tomography and [18F]FACT: comparison with [11C]PIB. Eur J Nucl Med Mol Imaging. 2014;41(4):745–54.

    Article  CAS  PubMed  Google Scholar 

  17. Barret O, Hannestad J, Vala C, Alagille D, Tavares A, Laruelle M, et al. Characterization in humans of 18F-MNI-444, a PET radiotracer for brain adenosine 2A receptors. J Nucl Med. 2015;56(4):586–91.

    Article  CAS  PubMed  Google Scholar 

  18. Akerele MI, Zein SA, Pandya S, Nikolopoulou A, Gauthier SA, Raj A, et al. Population-based input function for TSPO quantification and kinetic modeling with [(11)C]-DPA-713. EJNMMI Phys. 2021;8(1):39.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Choi JY, Lyoo CH, Kim JS, Kim KM, Kang JH, Choi SH, et al. 18F-Mefway PET imaging of serotonin 1A receptors in humans: a comparison with 18F-FCWAY. PLoS ONE. 2015;10(4): e0121342.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Logan J, Fowler JS, Volkow ND, Wolf AP, Dewey SL, Schlyer DJ, et al. Graphical analysis of reversible radioligand binding from time-activity measurements applied to [N-11C-methyl]-(-)-cocaine PET studies in human subjects. J Cereb Blood Flow Metab. 1990;10(5):740–7.

    Article  CAS  PubMed  Google Scholar 

  21. Hillmer AT, Li S, Zheng MQ, Scheunemann M, Lin SF, Nabulsi N, et al. PET imaging of alpha(7) nicotinic acetylcholine receptors: a comparative study of [(18)F]ASEM and [(18)F]DBT-10 in nonhuman primates, and further evaluation of [(18)F]ASEM in humans. Eur J Nucl Med Mol Imaging. 2017;44(6):1042–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Kimura Y, Takahata K, Shimazaki T, Kitamura S, Seki C, Ikoma Y, et al. Pharmacokinetic and pharmacodynamic assessment of histamine H(3) receptor occupancy by enerisant: a human PET study with a novel H(3) binding ligand, [(11)C]TASP457. Eur J Nucl Med Mol Imaging. 2022;49(4):1127–35.

    Article  CAS  PubMed  Google Scholar 

  23. Naganawa M, Jacobsen LK, Zheng MQ, Lin SF, Banerjee A, Byon W, et al. Evaluation of the agonist PET radioligand [(1)(1)C]GR103545 to image kappa opioid receptor in humans: kinetic model selection, test-retest reproducibility and receptor occupancy by the antagonist PF-04455242. Neuroimage. 2014;1(99):69–79.

    Article  Google Scholar 

  24. Naganawa M, Waterhouse RN, Nabulsi N, Lin SF, Labaree D, Ropchan J, et al. First-in-human assessment of the novel PDE2A PET radiotracer 18F-PF-05270430. J Nucl Med. 2016;57(9):1388–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Naganawa M, Nabulsi N, Planeta B, Gallezot JD, Lin SF, Najafzadeh S, et al. Tracer kinetic modeling of [(11)C]AFM, a new PET imaging agent for the serotonin transporter. J Cereb Blood Flow Metab. 2013;33(12):1886–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Ichise M, Toyama H, Innis RB, Carson RE. Strategies to improve neuroreceptor parameter estimation by linear regression analysis. J Cereb Blood Flow Metab. 2002;22(10):1271–81.

    Article  PubMed  Google Scholar 

  27. Parsey RV, Ogden RT, Mann JJ. Determination of volume of distribution using likelihood estimation in graphical analysis: elimination of estimation bias. J Cereb Blood Flow Metab. 2003;23(12):1471–8.

    Article  PubMed  Google Scholar 

  28. Kramer V, Juri C, Riss PJ, Pruzzo R, Soza-Ried C, Flores J, et al. Pharmacokinetic evaluation of [(18)F]PR04.MZ for PET/CT imaging and quantification of dopamine transporters in the human brain. Eur J Nucl Med Mol Imaging. 2020;47(8):1927–37.

    Article  CAS  PubMed  Google Scholar 

  29. Van Laere KJ, Sanabria-Bohorquez SM, Mozley DP, Burns DH, Hamill TG, Van Hecken A, et al. (11)C-MK-8278 PET as a tool for pharmacodynamic brain occupancy of histamine 3 receptor inverse agonists. J Nucl Med. 2014;55(1):65–72.

    Article  PubMed  Google Scholar 

  30. Naganawa M, Zheng MQ, Nabulsi N, Tomasi G, Henry S, Lin SF, et al. Kinetic modeling of (11)C-LY2795050, a novel antagonist radiotracer for PET imaging of the kappa opioid receptor in humans. J Cereb Blood Flow Metab. 2014;34(11):1818–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Kramer V, Dyssegaard A, Flores J, Soza-Ried C, Rosch F, Knudsen GM, et al. Characterization of the serotonin 2A receptor selective PET tracer (R)-[(18)F]MH.MZ in the human brain. Eur J Nucl Med Mol Imaging. 2020;47(2):355–65.

    Article  CAS  PubMed  Google Scholar 

  32. Marner L, Gillings N, Comley RA, Baare WF, Rabiner EA, Wilson AA, et al. Kinetic modeling of 11C-SB207145 binding to 5-HT4 receptors in the human brain in vivo. J Nucl Med. 2009;50(6):900–8.

    Article  CAS  PubMed  Google Scholar 

  33. Lammertsma AA, Hume SP. Simplified reference tissue model for PET receptor studies. Neuroimage. 1996;4(3 Pt 1):153–8.

    Article  CAS  PubMed  Google Scholar 

  34. Grunder G, Siessmeier T, Lange-Asschenfeldt C, Vernaleken I, Buchholz HG, Stoeter P, et al. [18F]Fluoroethylflumazenil: a novel tracer for PET imaging of human benzodiazepine receptors. Eur J Nucl Med. 2001;28(10):1463–70.

    Article  CAS  PubMed  Google Scholar 

  35. Cunningham VJ, Jones T. Spectral analysis of dynamic PET studies. J Cereb Blood Flow Metab. 1993;13(1):15–23.

    Article  CAS  PubMed  Google Scholar 

  36. Wey HY, Gilbert TM, Zurcher NR, She A, Bhanot A, Taillon BD, et al. Insights into neuroepigenetics through human histone deacetylase PET imaging. Sci Transl Med. 2016;8(351):351ra106.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Miederer I, Shi K, Wendler T. Machine learning methods for tracer kinetic modelling. Nuklearmedizin. 2023;62(6):370–8.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This study was partly supported by the Naito Foundation, Japan (MS) research grant.

Author information

Authors and Affiliations

  1. Department of Quantum Science and Energy Engineering, Graduate School of Engineering, Tohoku University, Sendai, Japan

    Itsuki Miyajima, Ayano Yoshikawa, Kyosei Sahashi & Miho Shidahara

  2. Advanced Neuroimaging Center, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan

    Chie Seki & Yuji Nagai

  3. Division of Radiation Protection and Nuclear Safety, Research Center for Accelerator and Radioisotope Science, Tohoku University, Sendai, Japan

    Hiroshi Watabe

Authors
  1. Itsuki Miyajima
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  2. Ayano Yoshikawa
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  3. Kyosei Sahashi
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  4. Chie Seki
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  6. Hiroshi Watabe
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  7. Miho Shidahara
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Correspondence to Miho Shidahara.

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Miyajima, I., Yoshikawa, A., Sahashi, K. et al. DOCK–PET: database of CNS kinetic parameters in the healthy human brain for existing PET tracers. Ann Nucl Med (2024). https://doi.org/10.1007/s12149-024-01947-z

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  • DOI: https://doi.org/10.1007/s12149-024-01947-z

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