Program Information
A Biophysical Model for Non-Invasive Imaging of Drug Transport in Solid Tumors
N Sinno1,2*, B Driscoll2 , C Coolens1,2,3 , (1) University of Toronto, Toronto, ON, (2) Princess Margaret Cancer Centre, University Health Network, Toronto, ON, (3) TECHNA Institute, University Health Network, Toronto, ON
Presentations
SU-K-702-4 (Sunday, July 30, 2017) 4:00 PM - 6:00 PM Room: 702
Purpose: To create and validate a mathematical model for non-invasive imaging of iodixanol transport in solid tumors in order to improve the understanding of convective and diffusive forces in the interstitium. Analyzing fluid flow on a cross-voxel level allowed an improved insight into physical processes governing fluid transport in the tumor.
Methods: The transport model developed combines the conservation of mass equation and Modified Tofts Model. It includes the inevitable diffusion and convection across voxels addressing the lack of mass conservation in existing transport models.Second, the accuracy of the model in estimating tracer kinetics was assessed using a flow phantom designed to produce different time enhancement curves by adjusting the settings of the experiment (flow rate, exchange ratio). This provides the flexibility to produce time enhancement curves corresponding to various vascular networks around tumor regions. The developed model was fit to the concentration curves to deduce transport parameters including velocity values, diffusion coefficients and perfusion parameters. Model results are compared to the known phantom parameters and geometry.
Results: Fitting the model to measured concentration curves resulted in estimations of velocity, diffusion and perfusion values. The velocity parameters deduced are within the known fluid flow velocity range in the phantom. Two calculated fractional volumes are in line within 1.30% and 1.99% error. Perfusion parameters were calculated and analyzed. Diffusion parameters are off by orders of magnitude due to the high convection rates in the phantom relative to the diffusion rates.
Conclusion: The model succeeds in the characterization of convection forces and perfusion parameters. When applied to patients, it will allow an improved understanding of the forces driving iodixanol transport and overcomes limitations noticeable in existing transport models pertaining to the consideration of cross-voxel transport. Additional work is needed to accurately quantify diffusive forces in cases where convection dominates.
Funding Support, Disclosures, and Conflict of Interest: Source of funding: NSERC Discovery Grant
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