Madjid Soltani1,2, Mostafa Sefidgar3, Hossein Bazmara3, Michael E Casey4, Rathan M Subramaniam5, Richard L Wahl6, Arman Rahmim7,8. 1. Division of Nuclear Medicine, Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, 21287, USA. msoltani@jhu.edu. 2. Department of Mechanical Engineering, KNT University, Tehran, Iran. msoltani@jhu.edu. 3. Department of Mechanical Engineering, Pardis Branch, Islamic Azad University, Pardis, Iran. 4. Siemens Medical Solutions, Knoxville, TN, 37932, USA. 5. Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA. 6. Department of Radiology, Washington University, St. Louis, MO, 63110, USA. 7. Division of Nuclear Medicine, Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, 21287, USA. arahmim1@jhmi.edu. 8. Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA. arahmim1@jhmi.edu.
Abstract
OBJECTIVE: Distribution of PET tracer uptake is elaborately modeled via a general equation used for solute transport modeling. This model can be used to incorporate various transport parameters of a solid tumor such as hydraulic conductivity of the microvessel wall, transvascular permeability as well as interstitial space parameters. This is especially significant because tracer delivery and drug delivery to solid tumors are determined by similar underlying tumor transport phenomena, and quantifying the former can enable enhanced prediction of the latter. METHODS: We focused on the commonly utilized FDG PET tracer. First, based on a mathematical model of angiogenesis, the capillary network of a solid tumor and normal tissues around it were generated. The coupling mathematical method, which simultaneously solves for blood flow in the capillary network as well as fluid flow in the interstitium, is used to calculate pressure and velocity distributions. Subsequently, a comprehensive spatiotemporal distribution model (SDM) is applied to accurately model distribution of PET tracer uptake, specifically FDG in this work, within solid tumors. RESULTS: The different transport mechanisms, namely convention and diffusion from vessel to tissue and in tissue, are elaborately calculated across the domain of interest and effect of each parameter on tracer distribution is investigated. The results show the convection terms to have negligible effect on tracer transport and the SDM can be solved after eliminating these terms. CONCLUSION: The proposed framework of spatiotemporal modeling for PET tracers can be utilized to comprehensively assess the impact of various parameters on the spatiotemporal distribution of PET tracers.
OBJECTIVE: Distribution of PET tracer uptake is elaborately modeled via a general equation used for solute transport modeling. This model can be used to incorporate various transport parameters of a solid tumor such as hydraulic conductivity of the microvessel wall, transvascular permeability as well as interstitial space parameters. This is especially significant because tracer delivery and drug delivery to solid tumors are determined by similar underlying tumor transport phenomena, and quantifying the former can enable enhanced prediction of the latter. METHODS: We focused on the commonly utilized FDG PET tracer. First, based on a mathematical model of angiogenesis, the capillary network of a solid tumor and normal tissues around it were generated. The coupling mathematical method, which simultaneously solves for blood flow in the capillary network as well as fluid flow in the interstitium, is used to calculate pressure and velocity distributions. Subsequently, a comprehensive spatiotemporal distribution model (SDM) is applied to accurately model distribution of PET tracer uptake, specifically FDG in this work, within solid tumors. RESULTS: The different transport mechanisms, namely convention and diffusion from vessel to tissue and in tissue, are elaborately calculated across the domain of interest and effect of each parameter on tracer distribution is investigated. The results show the convection terms to have negligible effect on tracer transport and the SDM can be solved after eliminating these terms. CONCLUSION: The proposed framework of spatiotemporal modeling for PET tracers can be utilized to comprehensively assess the impact of various parameters on the spatiotemporal distribution of PET tracers.