Multi-scale computational modeling towards efficacy in radiopharmaceutical therapies while minimizing side effects: Modeling of amino acid infusion

dc.contributor.authorGolzaryan, Aryan
dc.contributor.authorSouri, Mohammad
dc.contributor.authorKashkooli, Farshad M.
dc.contributor.authorRahmim, Arman
dc.contributor.authorSoltani, M.
dc.date.accessioned2026-05-29T17:45:53Z
dc.date.available2026-05-29T17:45:53Z
dc.date.issued2025-07-16
dc.description© 2025 Golzaryan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.description.abstractAmino acid infusion (AAI) is a technique used in radiopharmaceutical therapy (RPT) to reduce toxicity in kidney and increase clearance rate of radiopharmaceuticals from body. In this study our aim is to evaluate its effect in personalized RPT considering kidney and salivary glands as dose limiting organs using a multiscale modeling framework. We developed a Physiologically-Based Pharmacokinetic (PBPK) model consisting of 19 compartments, personalized it for four prostate cancer patients using data derived from gamma camera imaging. This model was used to investigate the influence of AAI on the absorbed dose to tumors and organs at risk. We then computed the maximum safe injected activity based on the PBPK model. To address the effects of interstitial fluid pressure (IFP) and tumor heterogeneity, we coupled the PBPK model with convection-diffusion-reaction (CDR) equations. To compare the effectiveness of our modeling approaches, we calculated absorbed doses to the tumors with and without AAI, using both the standalone PBPK model and the coupled PBPK-CDR model. Our findings revealed a relative error (RE) of 9.6% ± 2.2% (mean ± SD) in total tumor absorbed dose calculation between PBPK and CDR equations, attributable to the consideration of IFP. Moreover, AAI proved beneficial for RPT when the kidney was designated as the organ-at-risk. It enabled an increase in radiopharmaceutical injection from 12.3 ± 6.32 MBq (mean ± SD) to 15.45 ± 6.95 MBq (RE: 28.5% ± 15.7%), resulting in a corresponding increase in tumor absorbed dose from 67.8 ± 47.45 Gy to 72.43 ± 51.03 Gy (RE: 8.6% ± 5.4%), while maintaining critical kidney absorbed dose limits. However, this was not observed when the salivary gland was considered the dose-limiting organ. Although, AAI allowed for increased therapeutic injection ranging from 4.22 ± 2.23 MBq to 5.25 ± 3.14 MBq (RE: 19.2% ± 9.9%), it results in a minimal increase in tumor absorbed dose of 0.22 ± 0.04 (RE: 1.4% ± 1.3%). Statistical analysis using the Wilcoxon Signed-Rank Test revealed significant effects of AAI on administered activity and tumor absorbed dose (p-value = 0.007 < 0.05). Finally, a local sensitivity analysis was performed on selected radiation and tumor transportation parameters individually to evaluate their impact on the tumor absorbed dose. In conclusion, selection of organ-at-risk in personalized RPT is critical, as it determines the injected activity amount and the efficacy of delivery-enhancing techniques.
dc.identifier.urihttps://doi.org/10.1371/journal.pcbi.1013247
dc.identifier.urihttps://hdl.handle.net/10012/23455
dc.language.isoen
dc.publisherPublic Library of Science
dc.relation.ispartofseriesPLoS Computational Biology; 21(7); e1013247
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectradiopharmaceuticals
dc.subjectcancers and neoplasms
dc.subjectcancer treatment
dc.subjectprostate cancer
dc.subjectrenal cancer
dc.subjectmalignant tumors
dc.subjectkidneys
dc.subjectsalivary glands
dc.titleMulti-scale computational modeling towards efficacy in radiopharmaceutical therapies while minimizing side effects: Modeling of amino acid infusion
dc.typeArticle
dcterms.bibliographicCitationGolzaryan A, Souri M, Kashkooli FM, Rahmim A, Soltani M (2025) Multi-scale computational modeling towards efficacy in radiopharmaceutical therapies while minimizing side effects: Modeling of amino acid infusion. PLoS Comput Biol 21(7): e1013247. https://doi.org/10.1371/journal.pcbi.1013247
uws.contributor.affiliation1Faculty of Engineering
uws.contributor.affiliation2Electrical and Computer Engineering
uws.peerReviewStatusReviewed
uws.scholarLevelFaculty
uws.typeOfResourceTexten

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