Prediction of time-integrated activity coefficients in PRRT using simulated dynamic PET and a pharmacokinetic model |
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| Institution: | 1. Medical Radiation Physics/Radiation Protection, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany;2. Department of Electrical Engineering, Universitas Padjadjaran, Bandung, Indonesia;3. Department of Radiation Oncology, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany;4. Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany;5. Klinik für Nuklearmedizin, University Hospital, RWTH Aachen University, Aachen, Germany;6. Department of Nuclear Medicine, Maastricht University Medical Center (MUMC+), Maastricht, The Netherlands;1. Departamento de Fisiología Médica y Biofísica, Universidad de Sevilla, Spain;2. Servicio de Radiofísica, Hospital Universitario Virgen Macarena, Sevilla, Spain;3. Instituto de Física, Pontificia Universidad Católica de Chile, Santiago de Chile, Chile;4. Istituto Nazionale di Fisica Nucleare, Frascati, Italy;1. International Atomic Energy Agency, Department of Nuclear Sciences and Applications, Division of Human Health, Dosimetry and Medical Radiation Physics Section, Vienna International Centre, PO Box 100, A-1400 Vienna, Austria;2. Technische Universität München, Klinikum Rechts der Isar, Klinik für Strahlentherapie und Radiologische Onkologie, Ismaninger Str.22, D-81675 Munich, Germany;3. Centers for Disease Control and Prevention, Radiation Studies Branch, Div. of Environmental Hazards and Health Effects, National Center for Environmental Health, 4770 Buford Highway, NE, Atlanta 30341-3717, GA, United States;4. International Atomic Energy Agency, Department of Nuclear Safety and Security, Division of Radiation, Office of the Deputy Director General, Incident and Emergency Centre, Vienna International Centre, PO Box 100, A-1400 Vienna, Austria;5. Medical and Technical Director REAC/TS and Clinical Professor, Department of Therapeutic Radiology, Yale University School of Medicine Radiation Emergency Assistance Center/Training Site, P.O. Box 117, MS 39, Oak Ridge, TN 37831, United States;6. Executive Officer, National Institutes for Quantum and Radiological Science and Technology (QST) 4-9-1 Anagawa, Inage-ku, Chiba-city, Chiba 263-8555, Japan;7. International Atomic Energy Agency, Department of Nuclear Safety and Security, Division of Radiation, Transport and Waste Safety, Radiation Safety and Monitoring Section, Radiation Protection of Patients Unit, Vienna International Centre, PO Box 100, A-1400 Vienna, Austria;8. Department of Radiation Health Management, Fukushima Medical University, Fukushima 960-1295, Japan;1. German Cancer Research Center (DKFZ), Division of Medical Physics in Radiation Oncology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany;2. National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany;3. Heidelberg University Hospital, Department of Radiation Oncology, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany;4. Advacam s.r.o., Na Balkáně 2075/70, 130 00 Praha 3, Czech Republic;5. Institute of Experimental and Applied Physics, Czech Technical University in Prague, Horská 3a/22, 12800 Prague 2, Czech Republic;1. Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan;2. Faculty of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan;3. Department of Health Sciences, School of Medicine, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan;4. Department of Medical Technology, Kyushu University Hospital, 3-1-1, Maidashi, Higashi-ku, Fukuoka 812-8582, Japan;5. Saga Heavy Ion Medical Accelerator in Tosu, 415, Harakoga-cho, Tosu 841-0071, Japan |
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| Abstract: | PurposeTo 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.MethodsPBPK 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.ResultsFor 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%).ConclusionTreatment planning of PRRT based on dynamic PET data seems possible for the kidneys, liver and spleen using a PBPK model and patient specific information. |
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| Keywords: | PBPK model PRRT treatment planning Dynamic PET PET noise model |
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