Computational modeling of PET tracer distribution in solid tumors integrating microvasculature

Abstract Background We present computational modeling of positron emission tomography radiotracer uptake with consideration of blood flow and interstitial fluid flow, performing spatiotemporally-coupled modeling of uptake and integrating the microvasculature. In our mathematical modeling, the uptake...

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Autores principales:	Niloofar Fasaeiyan, M. Soltani, Farshad Moradi Kashkooli, Erfan Taatizadeh, Arman Rahmim
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Solid tumor Positron Emission Tomography (PET) Microvascular network FDG radiotracer Convection–Diffusion-Reaction modeling Biotechnology TP248.13-248.65
Acceso en línea:	https://doaj.org/article/479d7c223232473992203d2af701ae25
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spelling	oai:doaj.org-article:479d7c223232473992203d2af701ae252021-11-28T12:29:11ZComputational modeling of PET tracer distribution in solid tumors integrating microvasculature10.1186/s12896-021-00725-31472-6750https://doaj.org/article/479d7c223232473992203d2af701ae252021-11-01T00:00:00Zhttps://doi.org/10.1186/s12896-021-00725-3https://doaj.org/toc/1472-6750Abstract Background We present computational modeling of positron emission tomography radiotracer uptake with consideration of blood flow and interstitial fluid flow, performing spatiotemporally-coupled modeling of uptake and integrating the microvasculature. In our mathematical modeling, the uptake of fluorodeoxyglucose F-18 (FDG) was simulated based on the Convection–Diffusion–Reaction equation given its high accuracy and reliability in modeling of transport phenomena. In the proposed model, blood flow and interstitial flow are solved simultaneously to calculate interstitial pressure and velocity distribution inside cancer and normal tissues. As a result, the spatiotemporal distribution of the FDG tracer is calculated based on velocity and pressure distributions in both kinds of tissues. Results Interstitial pressure has maximum value in the tumor region compared to surrounding tissue. In addition, interstitial fluid velocity is extremely low in the entire computational domain indicating that convection can be neglected without effecting results noticeably. Furthermore, our results illustrate that the total concentration of FDG in the tumor region is an order of magnitude larger than in surrounding normal tissue, due to lack of functional lymphatic drainage system and also highly-permeable microvessels in tumors. The magnitude of the free tracer and metabolized (phosphorylated) radiotracer concentrations followed very different trends over the entire time period, regardless of tissue type (tumor vs. normal). Conclusion Our spatiotemporally-coupled modeling provides helpful tools towards improved understanding and quantification of in vivo preclinical and clinical studies.Niloofar FasaeiyanM. SoltaniFarshad Moradi KashkooliErfan TaatizadehArman RahmimBMCarticleSolid tumorPositron Emission Tomography (PET)Microvascular networkFDG radiotracerConvection–Diffusion-Reaction modelingBiotechnologyTP248.13-248.65ENBMC Biotechnology, Vol 21, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Solid tumor Positron Emission Tomography (PET) Microvascular network FDG radiotracer Convection–Diffusion-Reaction modeling Biotechnology TP248.13-248.65
spellingShingle	Solid tumor Positron Emission Tomography (PET) Microvascular network FDG radiotracer Convection–Diffusion-Reaction modeling Biotechnology TP248.13-248.65 Niloofar Fasaeiyan M. Soltani Farshad Moradi Kashkooli Erfan Taatizadeh Arman Rahmim Computational modeling of PET tracer distribution in solid tumors integrating microvasculature
description	Abstract Background We present computational modeling of positron emission tomography radiotracer uptake with consideration of blood flow and interstitial fluid flow, performing spatiotemporally-coupled modeling of uptake and integrating the microvasculature. In our mathematical modeling, the uptake of fluorodeoxyglucose F-18 (FDG) was simulated based on the Convection–Diffusion–Reaction equation given its high accuracy and reliability in modeling of transport phenomena. In the proposed model, blood flow and interstitial flow are solved simultaneously to calculate interstitial pressure and velocity distribution inside cancer and normal tissues. As a result, the spatiotemporal distribution of the FDG tracer is calculated based on velocity and pressure distributions in both kinds of tissues. Results Interstitial pressure has maximum value in the tumor region compared to surrounding tissue. In addition, interstitial fluid velocity is extremely low in the entire computational domain indicating that convection can be neglected without effecting results noticeably. Furthermore, our results illustrate that the total concentration of FDG in the tumor region is an order of magnitude larger than in surrounding normal tissue, due to lack of functional lymphatic drainage system and also highly-permeable microvessels in tumors. The magnitude of the free tracer and metabolized (phosphorylated) radiotracer concentrations followed very different trends over the entire time period, regardless of tissue type (tumor vs. normal). Conclusion Our spatiotemporally-coupled modeling provides helpful tools towards improved understanding and quantification of in vivo preclinical and clinical studies.
format	article
author	Niloofar Fasaeiyan M. Soltani Farshad Moradi Kashkooli Erfan Taatizadeh Arman Rahmim
author_facet	Niloofar Fasaeiyan M. Soltani Farshad Moradi Kashkooli Erfan Taatizadeh Arman Rahmim
author_sort	Niloofar Fasaeiyan
title	Computational modeling of PET tracer distribution in solid tumors integrating microvasculature
title_short	Computational modeling of PET tracer distribution in solid tumors integrating microvasculature
title_full	Computational modeling of PET tracer distribution in solid tumors integrating microvasculature
title_fullStr	Computational modeling of PET tracer distribution in solid tumors integrating microvasculature
title_full_unstemmed	Computational modeling of PET tracer distribution in solid tumors integrating microvasculature
title_sort	computational modeling of pet tracer distribution in solid tumors integrating microvasculature
publisher	BMC
publishDate	2021
url	https://doaj.org/article/479d7c223232473992203d2af701ae25
work_keys_str_mv	AT niloofarfasaeiyan computationalmodelingofpettracerdistributioninsolidtumorsintegratingmicrovasculature AT msoltani computationalmodelingofpettracerdistributioninsolidtumorsintegratingmicrovasculature AT farshadmoradikashkooli computationalmodelingofpettracerdistributioninsolidtumorsintegratingmicrovasculature AT erfantaatizadeh computationalmodelingofpettracerdistributioninsolidtumorsintegratingmicrovasculature AT armanrahmim computationalmodelingofpettracerdistributioninsolidtumorsintegratingmicrovasculature
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Computational modeling of PET tracer distribution in solid tumors integrating microvasculature

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