title: Treatment planning in PRRT based on simulated PET data and a PBPK model. Determination of accuracy using a PET noise model.
abstract: OBJECTIVE
  To investigate the accuracy of treatment planning in peptide-receptor radionuclide therapy (PRRT) based on simulated PET data (using a PET noise model) and a physiologically based pharmacokinetic (PBPK) model.
  
  
  METHODS
  The parameters of a PBPK model were fitted to the biokinetic data of 15 patients. True mathematical phantoms of patients (MPPs) were the PBPK model with the fitted parameters. PET measurements after bolus injection of 150 MBq68Ga-DOTATATE were simulated for the true MPPs. PET noise with typical noise levels was added to the data (i.e. c = 0.3 [low], 3, 30 and 300 [high]). Organ activity data in the kidneys, tumour, liver and spleen were simulated at 0.5, 1 and 4 h p.i. PBPK model parameters were fitted to the simulated noisy PET data to derive the PET-predicted MPPs. Therapy was simulated assuming an infusion of 3.3 GBq of90Y-DOTATATE over 30 min. Time-integrated activity coefficients (TIACs) of simulated therapy in tumour, kidneys, liver, spleen and remainder were calculated from both, true MPPs (true TIACs) and predicted MPPs (predicted TIACs). Variability v between true TIACs and predicted TIACs were calculated and analysed. Variability ≤ 10 % was considered to be an accurate prediction.
  
  
  RESULTS
  For all noise level, variabilities for the kidneys, liver, and spleen showed an accurate prediction for TIACs, e.g. c = 300: vkidney= (5 ± 2)%, vliver= (5 ± 2)%, vspleen= (4 ± 2)%. However, tumour TIAC predictions were not accurate for all noise levels, e.g. c = 0.3: vtumour= (8 ± 5)%.
  
  
  CONCLUSIONS
  PET-based treatment planning with kidneys as the dose limiting organ seems possible for all reported noise levels using an adequate PBPK model and previous knowledge about the individual patient.
authors.forename: Deni
authors.initials: D
authors.lastname: Hardiansyah
authors.forename: Wei
authors.initials: W
authors.lastname: Guo
authors.forename: Ali Asgar
authors.initials: AA
authors.lastname: Attarwala
authors.forename: Peter
authors.initials: P
authors.lastname: Kletting
authors.forename: Felix M
authors.initials: FM
authors.lastname: Mottaghy
authors.affiliation: Prof. Dr. rer. nat. Gerhard Glatting, Medizinische Strahlenphysik, Klinik für Nuklearmedizin, Universität Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany, Tel.: + 4973150061340, E-mail: gerhard.glatting@uni-ulm.de.
authors.forename: Gerhard
authors.initials: G
authors.lastname: Glatting
mesh_terms: D000368:Aged; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008297:Male; D008657:Metabolic Clearance Rate; D008875:Middle Aged; D008954:Models, Biological; D018358:Neuroendocrine Tumors / Q000378:metabolism* / Q000532:radiotherapy*; D009928:Organ Specificity; D009942:Organometallic Compounds / Q000493:pharmacokinetics* / Q000627:therapeutic use*; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals / Q000493:pharmacokinetics / Q000627:therapeutic use; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D061089:Radiotherapy, Image-Guided / Q000379:methods; D059629:Signal-To-Noise Ratio; D014018:Tissue Distribution
chemical_list: D009942:Organometallic Compounds; D019275:Radiopharmaceuticals; C513399:gallium Ga 68 dotatate
keywords: PBPK Model; PET; PET noise model; PRRT