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Estimation of Tumor Tracer Kinetics Employing a Novel Cross Voxel Exchange Model

N Sinno1*, E Taylor1, M Milosevic1, D Jaffray2, C Coolens1 (1) Princess Margaret Cancer Centre, Toronto, ON, (2) UT MD Anderson Cancer Center, Houston, TX


(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

The quantification of tumor perfusion parameters is closely connected to tumor aggressiveness and treatment outcome. Tofts Model (TM) is the most widely used pharmacokinetic model allowing the estimation of perfusion properties of tumor tissues. It assumes that the perfusion of tumor tissue is achieved solely through the exchange of tracer between the capillaries and the tissue, ignoring the effects of extravascular diffusion and convection and through the tissue. This is often violated leading to the misinterpretation of derived perfusion parameters. An advanced Cross-Voxel Exchange Model (CVXM) is proposed for the quantification of cross-voxel tracer kinetics and the evaluation of Tofts’ parameters.

First, in silico datasets were generated from the continuous CVXM model based on a range of known model parameters to investigate the interpretation of Tofts’ perfusion values. Secondly, transport parameters were derived from Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) of a TS-415 human cervical carcinoma xenograft by using TM and CVXM and compared.

The contribution of cross-voxel exchange to tracer transport and its effects on the interpretation of standard perfusion parameters are controlled by the diffusivity of tracer, the velocity of the fluid flow, the spatial distribution of blood vessels and the voxel dimensions. An equation developed gives the correct physiological interpretation of Tofts’ fitted parameters and predicts the deviations from the correct values. CVXM allows for the estimation of tracer velocity directly from DCE-MRI data.

For treatment decisions, caution must be exerted when interpreting Tofts’ perfusion parameters. The results support the need for utilizing CVXM to DCE-MRI in order to accurately determine metrics of tissue permeability and diffusivity of the tracer. This model promises a clearer understanding of the tumor microenvironment that can lead to enhanced personalized treatment planning.

Funding Support, Disclosures, and Conflict of Interest: Research was supported by the National Science and Research Council of Canada, the Ontario Institute of Cancer Research and the Robert and Andree Fitzhenry Brian Metastasis Program.


Perfusion Imaging, Modeling, Data Acquisition


IM/TH- Image Analysis (Single Modality or Multi-Modality): Quantitative imaging

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