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Abdollahi H, Yousefirizi F, Shiri I, Brosch-Lenz J, Mollaheydar E, Fele-Paranj A, Shi K, Zaidi H, Alberts I, Soltani M, Uribe C, Saboury B, Rahmim A. Theranostic digital twins: Concept, framework and roadmap towards personalized radiopharmaceutical therapies. Theranostics 2024; 14:3404-3422. [PMID: 38948052 PMCID: PMC11209714 DOI: 10.7150/thno.93973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Accepted: 04/22/2024] [Indexed: 07/02/2024] Open
Abstract
Radiopharmaceutical therapy (RPT) is a rapidly developing field of nuclear medicine, with several RPTs already well established in the treatment of several different types of cancers. However, the current approaches to RPTs often follow a somewhat inflexible "one size fits all" paradigm, where patients are administered the same amount of radioactivity per cycle regardless of their individual characteristics and features. This approach fails to consider inter-patient variations in radiopharmacokinetics, radiation biology, and immunological factors, which can significantly impact treatment outcomes. To address this limitation, we propose the development of theranostic digital twins (TDTs) to personalize RPTs based on actual patient data. Our proposed roadmap outlines the steps needed to create and refine TDTs that can optimize radiation dose to tumors while minimizing toxicity to organs at risk. The TDT models incorporate physiologically-based radiopharmacokinetic (PBRPK) models, which are additionally linked to a radiobiological optimizer and an immunological modulator, taking into account factors that influence RPT response. By using TDT models, we envisage the ability to perform virtual clinical trials, selecting therapies towards improved treatment outcomes while minimizing risks associated with secondary effects. This framework could empower practitioners to ultimately develop tailored RPT solutions for subgroups and individual patients, thus improving the precision, accuracy, and efficacy of treatments while minimizing risks to patients. By incorporating TDT models into RPTs, we can pave the way for a new era of precision medicine in cancer treatment.
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Affiliation(s)
- Hamid Abdollahi
- Department of Radiology, University of British Columbia, Vancouver, Canada
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
| | | | - Isaac Shiri
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
- Department of Cardiology, University Hospital Bern, Switzerland
| | - Julia Brosch-Lenz
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Elahe Mollaheydar
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Biomedical Engineering, University of British Columbia, Vancouver, Canada
| | - Ali Fele-Paranj
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Biomedical Engineering, University of British Columbia, Vancouver, Canada
- Department of Mathematics, University of British Columbia, Vancouver, Canada
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Informatics, Technical University of Munich, Munich, Germany
| | - Habib Zaidi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark
- University Research and Innovation Center, Óbuda University, Budapest, Hungary
| | - Ian Alberts
- Department of Molecular Imaging and Therapy, BC Cancer, Vancouver, Canada
| | - Madjid Soltani
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
- Department of Electrical and Computer Engineering, University of Waterloo, ON, Canada
| | - Carlos Uribe
- Department of Radiology, University of British Columbia, Vancouver, Canada
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Molecular Imaging and Therapy, BC Cancer, Vancouver, Canada
| | - Babak Saboury
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, USA
| | - Arman Rahmim
- Department of Radiology, University of British Columbia, Vancouver, Canada
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, Canada
- Department of Biomedical Engineering, University of British Columbia, Vancouver, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
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Siebinga H, de Wit-van der Veen BJ, de Vries-Huizing DMV, Vogel WV, Hendrikx JJMA, Huitema ADR. Quantification of biochemical PSA dynamics after radioligand therapy with [ 177Lu]Lu-PSMA-I&T using a population pharmacokinetic/pharmacodynamic model. EJNMMI Phys 2024; 11:39. [PMID: 38656678 PMCID: PMC11043318 DOI: 10.1186/s40658-024-00642-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 04/12/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND There is an unmet need for prediction of treatment outcome or patient selection for [177Lu]Lu-PSMA therapy in patients with metastatic castration-resistant prostate cancer (mCRPC). Quantification of the tumor exposure-response relationship is pivotal for further treatment optimization. Therefore, a population pharmacokinetic (PK) model was developed for [177Lu]Lu-PSMA-I&T using SPECT/CT data and, subsequently, related to prostate-specific antigen (PSA) dynamics after therapy in patients with mCRPC using a pharmacokinetic/pharmacodynamic (PKPD) modelling approach. METHODS A population PK model was developed using quantitative SPECT/CT data (406 scans) of 76 patients who received multiple cycles [177Lu]Lu-PSMA-I&T (± 7.4 GBq with either two- or six-week interval). The PK model consisted of five compartments; central, salivary glands, kidneys, tumors and combined remaining tissues. Covariates (tumor volume, renal function and cycle number) were tested to explain inter-individual variability on uptake into organs and tumors. The final PK model was expanded with a PD compartment (sequential fitting approach) representing PSA dynamics during and after treatment. To explore the presence of a exposure-response relationship, individually estimated [177Lu]Lu-PSMA-I&T tumor concentrations were related to PSA changes over time. RESULTS The population PK model adequately described observed data in all compartments (based on visual inspection of goodness-of-fit plots) with adequate precision of parameters estimates (< 36.1% relative standard error (RSE)). A significant declining uptake in tumors (k14) during later cycles was identified (uptake decreased to 73%, 50% and 44% in cycle 2, 3 and 4-7, respectively, compared to cycle 1). Tumor growth (defined by PSA increase) was described with an exponential growth rate (0.000408 h-1 (14.2% RSE)). Therapy-induced PSA decrease was related to estimated tumor concentrations (MBq/L) using both a direct and delayed drug effect. The final model adequately captured individual PSA concentrations after treatment (based on goodness-of-fit plots). Simulation based on the final PKPD model showed no evident differences in response for the two different dosing regimens currently used. CONCLUSIONS Our population PK model accurately described observed [177Lu]Lu-PSMA-I&T uptake in salivary glands, kidneys and tumors and revealed a clear declining tumor uptake over treatment cycles. The PKPD model adequately captured individual PSA observations and identified population response rates for the two dosing regimens. Hence, a PKPD modelling approach can guide prediction of treatment response and thus identify patients in whom radioligand therapy is likely to fail.
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Affiliation(s)
- Hinke Siebinga
- Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute: Antoni Van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
- Department of Nuclear Medicine, The Netherlands Cancer Institute: Antoni Van Leeuwenhoek, Amsterdam, The Netherlands.
| | | | - Daphne M V de Vries-Huizing
- Department of Nuclear Medicine, The Netherlands Cancer Institute: Antoni Van Leeuwenhoek, Amsterdam, The Netherlands
| | - Wouter V Vogel
- Department of Nuclear Medicine, The Netherlands Cancer Institute: Antoni Van Leeuwenhoek, Amsterdam, The Netherlands
- Department of Radiation Oncology, The Netherlands Cancer Institute: Antoni Van Leeuwenhoek, Amsterdam, The Netherlands
| | - Jeroen J M A Hendrikx
- Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute: Antoni Van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- Department of Nuclear Medicine, The Netherlands Cancer Institute: Antoni Van Leeuwenhoek, Amsterdam, The Netherlands
| | - Alwin D R Huitema
- Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute: Antoni Van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Pharmacology, Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
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Piranfar A, Moradi Kashkooli F, Zhan W, Bhandari A, Saboury B, Rahmim A, Soltani M. Radiopharmaceutical transport in solid tumors via a 3-dimensional image-based spatiotemporal model. NPJ Syst Biol Appl 2024; 10:39. [PMID: 38609421 PMCID: PMC11015041 DOI: 10.1038/s41540-024-00362-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 03/27/2024] [Indexed: 04/14/2024] Open
Abstract
Lutetium-177 prostate-specific membrane antigen (177Lu-PSMA)-targeted radiopharmaceutical therapy is a clinically approved treatment for patients with metastatic castration-resistant prostate cancer (mCRPC). Even though common practice reluctantly follows "one size fits all" approach, medical community believes there is significant room for deeper understanding and personalization of radiopharmaceutical therapies. To pursue this aim, we present a 3-dimensional spatiotemporal radiopharmaceutical delivery model based on clinical imaging data to simulate pharmacokinetic of 177Lu-PSMA within the prostate tumors. The model includes interstitial flow, radiopharmaceutical transport in tissues, receptor cycles, association/dissociation with ligands, synthesis of PSMA receptors, receptor recycling, internalization of radiopharmaceuticals, and degradation of receptors and drugs. The model was studied for a range of values for injection amount (100-1000 nmol), receptor density (10-500 nmol•l-1), and recycling rate of receptors (10-4 to 10-1 min-1). Furthermore, injection type, different convection-diffusion-reaction mechanisms, characteristic time scales, and length scales are discussed. The study found that increasing receptor density, ligand amount, and labeled ligands improved radiopharmaceutical uptake in the tumor. A high receptor recycling rate (0.1 min-1) increased radiopharmaceutical concentration by promoting repeated binding to tumor cell receptors. Continuous infusion results in higher radiopharmaceutical concentrations within tumors compared to bolus administration. These insights are crucial for advancing targeted therapy for prostate cancer by understanding the mechanism of radiopharmaceutical distribution in tumors. Furthermore, measures of characteristic length and advection time scale were computed. The presented spatiotemporal tumor transport model can analyze different physiological parameters affecting 177Lu-PSMA delivery.
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Affiliation(s)
- Anahita Piranfar
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
| | | | - Wenbo Zhan
- School of Engineering, King's College, University of Aberdeen, Aberdeen, AB24 3UE, UK
| | - Ajay Bhandari
- Biofluids Research Lab, Department of Mechanical Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826004, India
| | - Babak Saboury
- Department of Computational Nuclear Oncology, Institute of Nuclear Medicine, Bethesda, MD, USA
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada
| | - Arman Rahmim
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada
- Departments of Radiology and Physics, University of British Columbia, Vancouver, BC, Canada
| | - M Soltani
- Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada.
- Centre for Biotechnology and Bioengineering (CBB), University of Waterloo, Waterloo, ON, Canada.
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Stokke C, Gnesin S, Tran-Gia J, Cicone F, Holm S, Cremonesi M, Blakkisrud J, Wendler T, Gillings N, Herrmann K, Mottaghy FM, Gear J. EANM guidance document: dosimetry for first-in-human studies and early phase clinical trials. Eur J Nucl Med Mol Imaging 2024; 51:1268-1286. [PMID: 38366197 PMCID: PMC10957710 DOI: 10.1007/s00259-024-06640-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/04/2024] [Indexed: 02/18/2024]
Abstract
The numbers of diagnostic and therapeutic nuclear medicine agents under investigation are rapidly increasing. Both novel emitters and novel carrier molecules require careful selection of measurement procedures. This document provides guidance relevant to dosimetry for first-in human and early phase clinical trials of such novel agents. The guideline includes a short introduction to different emitters and carrier molecules, followed by recommendations on the methods for activity measurement, pharmacokinetic analyses, as well as absorbed dose calculations and uncertainty analyses. The optimal use of preclinical information and studies involving diagnostic analogues is discussed. Good practice reporting is emphasised, and relevant dosimetry parameters and method descriptions to be included are listed. Three examples of first-in-human dosimetry studies, both for diagnostic tracers and radionuclide therapies, are given.
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Affiliation(s)
- Caroline Stokke
- Department of Diagnostic Physics and Computational Radiology, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.
- Department of Physics, University of Oslo, Oslo, Norway.
| | - Silvano Gnesin
- Institute of Radiation Physics, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Johannes Tran-Gia
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
| | - Francesco Cicone
- Nuclear Medicine Unit, Department of Experimental and Clinical Medicine, "Magna Graecia" University of Catanzaro, Catanzaro, Italy
| | - Søren Holm
- Department of Clinical Physiology and Nuclear Medicine, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Marta Cremonesi
- Department of Medical Imaging and Radiation Sciences, European Institute of Oncology, IRCCS, Milan, Italy
| | - Johan Blakkisrud
- Department of Diagnostic Physics and Computational Radiology, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Thomas Wendler
- Computer-Aided Medical Procedures and Augmented Reality, Technische Universität München, Munich, Germany
- Clinical Computational Medical Imaging Research, Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Augsburg, Augsburg, Germany
| | - Nic Gillings
- Department of Clinical Physiology and Nuclear Medicine, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Ken Herrmann
- Department of Nuclear Medicine, University of Duisburg-Essen, and German Cancer Consortium (DKTK)-University Hospital Essen, Essen, Germany
- National Center for Tumor Diseases (NCT), NCT West, Heidelberg, Germany
| | - Felix M Mottaghy
- Department of Radiology and Nuclear Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands
- Department of Nuclear Medicine, University Hospital RWTH Aachen, Aachen, Germany
| | - Jonathan Gear
- Joint Department of Physics, Royal Marsden NHSFT & Institute of Cancer Research, Sutton, UK
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Hardiansyah D, Yousefzadeh-Nowshahr E, Kind F, Beer AJ, Ruf J, Glatting G, Mix M. Single-Time-Point Renal Dosimetry Using Nonlinear Mixed-Effects Modeling and Population-Based Model Selection in [ 177Lu]Lu-PSMA-617 Therapy. J Nucl Med 2024; 65:566-572. [PMID: 38423787 DOI: 10.2967/jnumed.123.266268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 01/23/2024] [Indexed: 03/02/2024] Open
Abstract
The aim of this study was to investigate the accuracy of single-time-point (STP) renal dosimetry imaging using SPECT/CT data, a nonlinear mixed-effects (NLME) model, and a population-based model selection (PBMS) in a large population for 177Lu-labeled prostate-specific membrane antigen therapy. Methods: Biokinetic data (mean ± SD) of [177Lu]Lu-PSMA-617 in kidneys at time points 1 (1.8 ± 0.8 h), 2 (18.7 ± 0.9 h), 3 (42.6 ± 1.0 h), 4 (66.3 ± 0.9 h), and 5 (160.3 ± 24.2 h) after injection were obtained from 63 patients with metastatic castration-resistant prostate cancer using SPECT/CT. Thirteen functions were derived from various parameterizations of 1- to 5-exponential functions. The function's parameters were fitted in the NLME framework to the all-time-point (ATP) data. The PBMS NLME method was performed using the goodness-of-fit test and Akaike weight to select the best function fitting the data. The best function from ATP fitting was used to calculate the reference time-integrated activity and absorbed doses. In STP dosimetry, the parameters of a particular patient with STP data were fitted simultaneously to the STP data at different time points of that patient with ATP data of all other patients. The parameters from STP fitting were used to calculate the STP time-integrated activity and absorbed doses. Relative deviations (RDs) and root-mean-square errors (RMSEs) were used to analyze the accuracy of the calculated STP absorbed dose compared with the reference absorbed dose obtained from the best-fit ATP function. The performance of STP dosimetry using PBMS NLME modeling was compared with the Hänscheid and Madsen methods. Results: The function [Formula: see text] was selected as the best-fit ATP function, with an Akaike weight of 100%. For STP dosimetry, the STP measurement by SPECT/CT at time point 3 (42.6 ± 1.0 h) showed a relatively low mean RD of -4.4% ± 9.4% and median RD of -0.7%. Time point 3 had the lowest RMSE value compared with those at the other 4 time points. The RMSEs of the absorbed dose RDs for time points 1-5 were 23%, 16%, 10%, 20%, and 53%, respectively. The STP dosimetry using the PBMS NLME method outperformed the Hänscheid and Madsen methods for all investigated time points. Conclusion: Our results show that a single measurement of SPECT/CT at 2 d after injection might be used to calculate accurate kidney-absorbed doses using the NLME method and PBMS.
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Affiliation(s)
- Deni Hardiansyah
- Medical Physics and Biophysics, Physics Department, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia;
- Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany
| | - Elham Yousefzadeh-Nowshahr
- Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany
- Department of Nuclear Medicine, Ulm University, Ulm, Germany
| | - Felix Kind
- Department of Nuclear Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; and
| | - Ambros J Beer
- Department of Nuclear Medicine, Ulm University, Ulm, Germany
| | - Juri Ruf
- Department of Nuclear Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; and
| | - Gerhard Glatting
- Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany
- Department of Nuclear Medicine, Ulm University, Ulm, Germany
| | - Michael Mix
- Department of Nuclear Medicine, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; and
- Nuclear Medicine Division, Department of Medical Imaging and Clinical Oncology, Faculty of Medicine and Health Science, Stellenbosch University, Cape Town, South Africa
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Vasić V, Gustafsson J, Nowshahr EY, Stenvall A, Beer AJ, Gleisner KS, Glatting G. A PBPK model for PRRT with [ 177Lu]Lu-DOTA-TATE: Comparison of model implementations in SAAM II and MATLAB/SimBiology. Phys Med 2024; 119:103299. [PMID: 38367588 DOI: 10.1016/j.ejmp.2024.103299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/06/2023] [Accepted: 01/23/2024] [Indexed: 02/19/2024] Open
Abstract
Physiologically based pharmacokinetic (PBPK) models offer the ability to simulate and predict the biodistribution of radiopharmaceuticals and have the potential to enable individualised treatment planning in molecular radiotherapy. The objective of this study was to develop and implement a whole-body compartmental PBPK model for peptide receptor radionuclide therapy (PRRT) with [177Lu]Lu-DOTA-TATE in SimBiology to allow for more complex analyses. The correctness of the model implementation was ensured by comparing its outputs, such as the time-integrated activity (TIA), with those of a PBPK model implemented in SAAM II software. METHODS A combined PBPK model for [68Ga]Ga-DOTA-TATE and [177Lu]Lu-DOTA-TATE was developed and implemented in both SAAM II and SimBiology. A retrospective analysis of 12 patients with metastatic neuroendocrine tumours (NETs) was conducted. First, time-activity curves (TACs) and TIAs from the two software were calculated and compared for identical parameter values. Second, pharmacokinetic parameters were fitted to activity concentrations, analysed and compared. RESULTS The PBPK model implemented in SimBiology produced TIA results comparable to those generated by the model implemented in SAAM II, with a relative deviation of less than 0.5% when using the same input parameters. The relative deviation of the fitted TIAs was less than 5% when model parameter values were fitted to the measured activity concentrations. CONCLUSION The proposed PBPK model implemented in SimBiology can be used for dosimetry in radioligand therapy and TIA prediction. Its outputs are similar to those generated by the PBPK model implemented in SAAM II, confirming the correctness of the model implementation in SimBiology.
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Affiliation(s)
- Valentina Vasić
- Department of Nuclear Medicine, Ulm University, Ulm, Germany; Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany.
| | | | - Elham Yousefzadeh Nowshahr
- Department of Nuclear Medicine, Ulm University, Ulm, Germany; Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany
| | - Anna Stenvall
- Medical Radiation Physics, Lund University, Lund, Sweden
| | - Ambros J Beer
- Department of Nuclear Medicine, Ulm University, Ulm, Germany
| | | | - Gerhard Glatting
- Department of Nuclear Medicine, Ulm University, Ulm, Germany; Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany
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Fele-Paranj A, Saboury B, Uribe C, Rahmim A. Physiologically based radiopharmacokinetic (PBRPK) modeling to simulate and analyze radiopharmaceutical therapies: studies of non-linearities, multi-bolus injections, and albumin binding. EJNMMI Radiopharm Chem 2024; 9:6. [PMID: 38252191 PMCID: PMC10803696 DOI: 10.1186/s41181-023-00236-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 12/22/2023] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND We aimed to develop a publicly shared computational physiologically based pharmacokinetic (PBPK) model to reliably simulate and analyze radiopharmaceutical therapies (RPTs), including probing of hot-cold ligand competitions as well as alternative injection scenarios and drug designs, towards optimal therapies. RESULTS To handle the complexity of PBPK models (over 150 differential equations), a scalable modeling notation called the "reaction graph" is introduced, enabling easy inclusion of various interactions. We refer to this as physiologically based radiopharmacokinetic (PBRPK) modeling, fine-tuned specifically for radiopharmaceuticals. As three important applications, we used our PBRPK model to (1) study the effect of competition between hot and cold species on delivered doses to tumors and organs at risk. In addition, (2) we evaluated an alternative paradigm of utilizing multi-bolus injections in RPTs instead of prevalent single injections. Finally, (3) we used PBRPK modeling to study the impact of varying albumin-binding affinities by ligands, and the implications for RPTs. We found that competition between labeled and unlabeled ligands can lead to non-linear relations between injected activity and the delivered dose to a particular organ, in the sense that doubling the injected activity does not necessarily result in a doubled dose delivered to a particular organ (a false intuition from external beam radiotherapy). In addition, we observed that fractionating injections can lead to a higher payload of dose delivery to organs, though not a differential dose delivery to the tumor. By contrast, we found out that increased albumin-binding affinities of the injected ligands can lead to such a differential effect in delivering more doses to tumors, and this can be attributed to several factors that PBRPK modeling allows us to probe. CONCLUSIONS Advanced computational PBRPK modeling enables simulation and analysis of a variety of intervention and drug design scenarios, towards more optimal delivery of RPTs.
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Affiliation(s)
- Ali Fele-Paranj
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada
| | - Babak Saboury
- Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, Maryland, US
| | - Carlos Uribe
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada
- Department of Functional Imaging, BC Cancer, Vancouver, BC, Canada
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Arman Rahmim
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada.
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC, Canada.
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada.
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Ivashchenko OV, O'Doherty J, Hardiansyah D, Cremonesi M, Tran-Gia J, Hippeläinen E, Stokke C, Grassi E, Sandström M, Glatting G. Time-Activity data fitting in molecular Radiotherapy: Methodology and pitfalls. Phys Med 2024; 117:103192. [PMID: 38052710 DOI: 10.1016/j.ejmp.2023.103192] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 10/18/2023] [Accepted: 11/28/2023] [Indexed: 12/07/2023] Open
Abstract
Absorbed radiation doses are essential in assessing the effects, e.g. safety and efficacy, of radiopharmaceutical therapy (RPT). Patient-specific absorbed dose calculations in the target or the organ at risk require multiple inputs. These include the number of disintegrations in the organ, i.e. the time-integrated activities (TIAs) of the organs, as well as other parameters describing the process of radiation energy deposition in the target tissue (i.e. mean energy per disintegration, radiation dose constants, etc). TIAs are then estimated by incorporating the area under the radiopharmaceutical's time-activity curve (TAC), which can be obtained by quantitative measurements of the biokinetics in the patient (typically based on imaging data such as planar scintigraphy, SPECT/CT, PET/CT, or blood and urine samples). The process of TAC determination/calculation for RPT generally depends on the user, e.g., the chosen number and schedule of measured time points, the selection of the fit function, the error model for the data and the fit algorithm. These decisions can strongly affect the final TIA values and thus the accuracy of calculated absorbed doses. Despite the high clinical importance of the TIA values, there is currently no consensus on processing time-activity data or even a clear understanding of the influence of uncertainties and variations in personalised RPT dosimetry related to user-dependent TAC calculation. As a first step towards minimising site-dependent variability in RPT dosimetry, this work provides an overview of quality assurance and uncertainty management considerations of the TIA estimation.
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Affiliation(s)
- Oleksandra V Ivashchenko
- Department of Nuclear Medicine and Molecular Imaging, Medical Imaging Center, University Medical Center Groningen, the Netherlands.
| | - Jim O'Doherty
- Siemens Medical Solutions, Malvern, PA, United States of America; Department of Radiology & Radiological Science, Medical University of South Carolina, Charleston, SC, United States of America; Radiography & Diagnostic Imaging, University College Dublin, Dublin, Ireland
| | - Deni Hardiansyah
- Medical Physics and Biophysics Division, Physics Department, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia; Research Collaboration Centre for Theranostic Radiopharmaceuticals, BRIN, Bandung, Indonesia
| | - Marta Cremonesi
- Unit of Radiation Research, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Johannes Tran-Gia
- Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
| | - Eero Hippeläinen
- Department of Clinical Physiology and Nuclear Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Caroline Stokke
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway; Department of Physics, University of Oslo, Oslo, Norway
| | - Elisa Grassi
- Medical Physics Unit, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy
| | | | - Gerhard Glatting
- Medical Radiation Physics, Department of Nuclear Medicine, Ulm University, Ulm, Germany
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Abdollahi H, Saboury B, Soltani M, Shi K, Uribe C, Rahmim A. Radiopharmaceutical therapy on-a-chip: a perspective on microfluidic-driven digital twins towards personalized cancer therapies. Sci Bull (Beijing) 2023; 68:1983-1988. [PMID: 37573246 DOI: 10.1016/j.scib.2023.08.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/14/2023]
Affiliation(s)
- Hamid Abdollahi
- Department of Radiology, University of British Columbia, Vancouver V5Z 1M9, Canada; Department of Integrative Oncology, BC Cancer Research Institute, Vancouver V5Z 1L3, Canada
| | - Babak Saboury
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver V5Z 1L3, Canada; Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda 20892, USA
| | - Madjid Soltani
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver V5Z 1L3, Canada; Department of Electrical & Computer Engineering, University of Waterloo, Waterloo N2L 3G1, Canada
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, Bern 3010, Switzerland; Computer Aided Medical Procedures and Augmented Reality, Institute of Informatics, Technical University of Munich, Munich 80333, Germany
| | - Carlos Uribe
- Department of Radiology, University of British Columbia, Vancouver V5Z 1M9, Canada; Department of Integrative Oncology, BC Cancer Research Institute, Vancouver V5Z 1L3, Canada; Functional Imaging, BC Cancer, Vancouver V5Z 4E6, Canada
| | - Arman Rahmim
- Department of Radiology, University of British Columbia, Vancouver V5Z 1M9, Canada; Department of Integrative Oncology, BC Cancer Research Institute, Vancouver V5Z 1L3, Canada; Department of Physics & Astronomy, University of British Columbia, Vancouver V6T 1Z1, Canada.
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Siebinga H, de Wit-van der Veen BJ, Beijnen JH, Stokkel MPM, Dorlo TPC, Huitema ADR, Hendrikx JJMA. Predicting [ 177Lu]Lu-HA-DOTATATE kidney and tumor accumulation based on [ 68Ga]Ga-HA-DOTATATE diagnostic imaging using semi-physiological population pharmacokinetic modeling. EJNMMI Phys 2023; 10:48. [PMID: 37615812 PMCID: PMC10449733 DOI: 10.1186/s40658-023-00565-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 07/24/2023] [Indexed: 08/25/2023] Open
Abstract
BACKGROUND Prediction of [177Lu]Lu-HA-DOTATATE kidney and tumor uptake based on diagnostic [68Ga]Ga-HA-DOTATATE imaging would be a crucial step for precision dosing of [177Lu]Lu-HA-DOTATATE. In this study, the population pharmacokinetic (PK) differences between [177Lu]Lu-HA-DOTATATE and [68Ga]Ga-HA-DOTATATE were assessed and subsequently [177Lu]Lu-HA-DOTATATE was predicted based on [68Ga]Ga-HA-DOTATATE imaging. METHODS A semi-physiological nonlinear mixed-effects model was developed for [68Ga]Ga-HA-DOTATATE and [177Lu]Lu-HA-DOTATATE, including six compartments (representing blood, spleen, kidney, tumor lesions, other somatostatin receptor expressing organs and a lumped rest compartment). Model parameters were fixed based on a previously developed physiologically based pharmacokinetic model for [68Ga]Ga-HA-DOTATATE. For [177Lu]Lu-HA-DOTATATE, PK parameters were based on literature values or estimated based on scan data (four time points post-injection) from nine patients. Finally, individual [177Lu]Lu-HA-DOTATATE uptake into tumors and kidneys was predicted based on individual [68Ga]Ga-HA-DOTATATE scan data using Bayesian estimates. Predictions were evaluated compared to observed data using a relative prediction error (RPE) for both area under the curve (AUC) and absorbed dose. Lastly, to assess the predictive value of diagnostic imaging to predict therapeutic exposure, individual prediction RPEs (using Bayesian estimation) were compared to those from population predictions (using the population model). RESULTS Population uptake rate parameters for spleen, kidney and tumors differed by a 0.29-fold (15% relative standard error (RSE)), 0.49-fold (15% RSE) and 1.43-fold (14% RSE), respectively, for [177Lu]Lu-HA-DOTATATE compared to [68Ga]Ga-HA-DOTATATE. Model predictions adequately described observed data in kidney and tumors for both peptides (based on visual inspection of goodness-of-fit plots). Individual predictions of tumor uptake were better (RPE AUC -40 to 28%) compared to kidney predictions (RPE AUC -53 to 41%). Absorbed dose predictions were less predictive for both tumor and kidneys (RPE tumor and kidney -51 to 44% and -58 to 82%, respectively). For most patients, [177Lu]Lu-HA-DOTATATE tumor accumulation predictions based on individual PK parameters estimated from diagnostic imaging outperformed predictions based on population parameters. CONCLUSION Our semi-physiological PK model indicated clear differences in PK parameters for [68Ga]Ga-HA-DOTATATE and [177Lu]Lu-HA-DOTATATE. Diagnostic images provided additional information to individually predict [177Lu]Lu-HA-DOTATATE tumor uptake compared to using a population approach. In addition, individual predictions indicated that many aspects, apart from PK differences, play a part in predicting [177Lu]Lu-HA-DOTATATE distribution.
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Affiliation(s)
- Hinke Siebinga
- Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
- Department of Nuclear Medicine, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
- Graduate School of Life Sciences, Utrecht University, Utrecht, The Netherlands.
| | | | - Jos H Beijnen
- Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Marcel P M Stokkel
- Department of Nuclear Medicine, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Thomas P C Dorlo
- Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- Department of Pharmacy, Uppsala University, Uppsala, Sweden
| | - Alwin D R Huitema
- Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Pharmacology, Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Jeroen J M A Hendrikx
- Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
- Department of Nuclear Medicine, The Netherlands Cancer Institute, Amsterdam, The Netherlands
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Kovan B, Demir B, Işık EG, Has Şimşek D, Özkan ZG, Kuyumcu S, Türkmen C, Şanlı Y. An anthropomorphic body phantom for the determination of calibration factor in radionuclide treatment dosimetry. RADIATION PROTECTION DOSIMETRY 2023:ncad176. [PMID: 37334429 PMCID: PMC10372715 DOI: 10.1093/rpd/ncad176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 02/02/2023] [Accepted: 05/18/2023] [Indexed: 06/20/2023]
Abstract
The aim of this study is to create an inhomogeneous human-like phantom, whose attenuation and scattering effects are similar to the human body, as an alternative to the homogeneous phantoms traditionally used in calibration factor (CF) determination. The phantom was designed to include the thorax, abdomen and upper pelvis regions sized to represent a 75-kg male with a body mass index of 25. Measurements using Lu-177 with 50- and 100-mL lesion volumes were performed using inhomogeneous anthropomorphic body phantom (ABP) and homogeneous NEMA PET body phantom. There was a difference of 5.7% of Calibration Factor including attenuation and scatter effect between ABP and NEMA PET body phantom. Because it better reflects the attenuation and scatter effect, it is recommended to use a human-like inhomogeneous phantom for determination of CF instead of a homogeneous phantom.
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Affiliation(s)
- Bilal Kovan
- Istanbul Medical Faculty, Department of Nuclear Medicine, Istanbul University, Fatih 34080, Turkey
| | - Bayram Demir
- Science Faculty, Department of Physics, Istanbul University, Fatih34080, Turkey
| | - Emine Göknur Işık
- Istanbul Medical Faculty, Department of Nuclear Medicine, Istanbul University, Fatih 34080, Turkey
| | - Duygu Has Şimşek
- Istanbul Medical Faculty, Department of Nuclear Medicine, Istanbul University, Fatih 34080, Turkey
| | - Zeynep Gözde Özkan
- Istanbul Medical Faculty, Department of Nuclear Medicine, Istanbul University, Fatih 34080, Turkey
| | - Sekan Kuyumcu
- Istanbul Medical Faculty, Department of Nuclear Medicine, Istanbul University, Fatih 34080, Turkey
| | - Cüneyt Türkmen
- Istanbul Medical Faculty, Department of Nuclear Medicine, Istanbul University, Fatih 34080, Turkey
| | - Yasemin Şanlı
- Istanbul Medical Faculty, Department of Nuclear Medicine, Istanbul University, Fatih 34080, Turkey
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Barakat A, Santoro L, Vivien M, Kotzki PO, Deshayes E, Khier S. Clinical Pharmacokinetics of Radiopharmaceuticals from SPECT/CT Image Acquisition by Contouring in Patients with Gastroenteropancreatic Neuroendocrine Tumors: Lu-177 DOTATATE (Lutathera ®) Case. Eur J Drug Metab Pharmacokinet 2023:10.1007/s13318-023-00829-5. [PMID: 37184824 DOI: 10.1007/s13318-023-00829-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/19/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND AND OBJECTIVE Lu-177 DOTATATE (Lutathera®) is a radiolabeled analog of somatostatin administered intravenously in patients with somatostatin receptor-positive gastroenteropancreatic neuroendocrine tumors. Biodistribution of Lu-177 DOTATATE in tumor and healthy tissues can be monitored by serial post-injection scintigraphy imaging. Patient exposure to the drug is variable with the recommended fixed dosage, and hence there is a variable response to treatment. The aim of this work was to study the pharmacokinetics of Lu-177 DOTATATE by a population modeling approach, based on single-photon emission computed tomography (SPECT)/computed tomography (CT) images used as surrogate of plasma concentrations to study the interindividual variability and finally optimize an individual dosage. METHODS From a retrospective study, SPECT/CT images were acquired at 4 h, 24 h, 72 h, and 192 h postadministration. From these images, volumic activities were calculated in blood and bone marrow. An individual non-compartmental pharmacokinetic analysis was performed, and the mean pharmacokinetic parameters of each tissue were compared together and with reference data. Blood volumic activities were then used to perform a population pharmacokinetic analysis (NONMEM). RESULTS The pharmacokinetic parameters (non-compartmental analysis) obtained from blood (clearance [CL] = 2.65 L/h, volume of distribution at steady state [Vss] = 309 L, elimination half-life [t1/2] = 86.3 h) and bone marrow (CL =1.68 L/h, Vss = 233 L, t1/2 = 98.8 h) were statistically different from each other and from reference values (CL = 4.50 L/h, Vss = 460 L, t1/2 = 71.0 h) published in the literature. SPECT/CT blood images were used as a surrogate of plasma concentrations to develop a population pharmacokinetic model. Weight was identified as covariate on volume of the central compartment, reducing the interindividual variability of all population pharmacokinetic parameters. CONCLUSION This study is a proof of concept that obtaining pharmacokinetic parameters with image-based blood concentration is possible. Obtaining observed concentrations from SPECT/CT images, without the need for blood sampling, is a real advantage for the patient and the drug monitoring. Pharmacokinetic modeling could be combined with a deep learning model for automatic contouring and allow precise patient-specific dose adjustment in a non-invasive manner.
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Affiliation(s)
- Anissa Barakat
- Pharmacokinetics and Pharmacometrics Department, School of Pharmacy, UFR Pharmacie, Montpellier University, 15 Avenue Charles Flahault, 34000, Montpellier, France
- Probabilities and Statistics Department, Institut Montpelliérain Alexander Grothendieck (IMAG), CNRS, UMR 5149, Inria, Montpellier University, Montpellier, France
- Nuclear Medicine Department, Montpellier Cancer Institute, Montpellier University, Montpellier, France
| | - Lore Santoro
- Nuclear Medicine Department, Montpellier Cancer Institute, Montpellier University, Montpellier, France
- Institut de Recherche en Cancérologie de Montpellier (IRCM), INSERM U1194, Montpellier University, Montpellier, France
| | - Myrtille Vivien
- Biostatistics, Informatics and pharmaceutical physic Laboratory, School of Pharmacy, UFR Pharmacie, Montpellier University, 15 Av. Ch. Flahault, 34000, Montpellier, France
- Institute of Functional Genomic (IGF)- UMR 5203, INSERM U1191, Montpellier, France
| | - Pierre-Olivier Kotzki
- Nuclear Medicine Department, Montpellier Cancer Institute, Montpellier University, Montpellier, France
- Institut de Recherche en Cancérologie de Montpellier (IRCM), INSERM U1194, Montpellier University, Montpellier, France
| | - Emmanuel Deshayes
- Nuclear Medicine Department, Montpellier Cancer Institute, Montpellier University, Montpellier, France
- Institut de Recherche en Cancérologie de Montpellier (IRCM), INSERM U1194, Montpellier University, Montpellier, France
| | - Sonia Khier
- Pharmacokinetics and Pharmacometrics Department, School of Pharmacy, UFR Pharmacie, Montpellier University, 15 Avenue Charles Flahault, 34000, Montpellier, France.
- Probabilities and Statistics Department, Institut Montpelliérain Alexander Grothendieck (IMAG), CNRS, UMR 5149, Inria, Montpellier University, Montpellier, France.
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