Prediction of time-integrated activity coefficients in PRRT using simulated dynamic PET and a pharmacokinetic model

Deni Hardiansyah, Ali Asgar Attarwala, Peter Kletting, Felix M. Mottaghy, Gerhard Glatting

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Purpose To investigate the accuracy of predicted time-integrated activity coefficients (TIACs) in peptide-receptor radionuclide therapy (PRRT) using simulated dynamic PET data and a physiologically based pharmacokinetic (PBPK) model. Methods PBPK parameters were estimated using biokinetic data of 15 patients after injection of (152 ± 15) MBq of 111In-DTPAOC (total peptide amount (5.78 ± 0.25) nmol). True mathematical phantoms of patients (MPPs) were the PBPK model with the estimated parameters. Dynamic PET measurements were simulated as being done after bolus injection of 150 MBq 68Ga-DOTATATE using the true MPPs. Dynamic PET scans around 35 min p.i. (P1), 4 h p.i. (P2) and the combination of P1 and P2 (P3) were simulated. Each measurement was simulated with four frames of 5 min each and 2 bed positions. PBPK parameters were fitted to the PET data to derive the PET-predicted MPPs. Therapy was simulated assuming an infusion of 5.1 GBq of 90Y-DOTATATE over 30 min in both true and PET-predicted MPPs. TIACs of simulated therapy were calculated, true MPPs (true TIACs) and predicted MPPs (predicted TIACs) followed by the calculation of variabilities v. Results For P1 and P2 the population variabilities of kidneys, liver and spleen were acceptable (v < 10%). For the tumours and the remainders, the values were large (up to 25%). For P3, population variabilities for all organs including the remainder further improved, except that of the tumour (v > 10%). Conclusion Treatment planning of PRRT based on dynamic PET data seems possible for the kidneys, liver and spleen using a PBPK model and patient specific information.

Original languageEnglish
Pages (from-to)298-304
Number of pages7
JournalPhysica Medica
Publication statusPublished - Oct 2017


  • Dynamic PET
  • PBPK model
  • PET noise model
  • PRRT treatment planning


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