Estimation of permeability from optical observations in a model system of 3D ovarian cancer nodules subjected to fluidic shear stress (Conference Presentation)

Sepideh Afshar; Imran Rizvi; Walfre Franco

doi:10.1117/12.2510089

4 March 2019 Estimation of permeability from optical observations in a model system of 3D ovarian cancer nodules subjected to fluidic shear stress (Conference Presentation)

Sepideh Afshar, Imran Rizvi, Walfre Franco

Author Affiliations +

Proceedings Volume 10875, Microfluidics, BioMEMS, and Medical Microsystems XVII; 1087513 (2019) https://doi.org/10.1117/12.2510089
Event: SPIE BiOS, 2019, San Francisco, California, United States

Abstract

In ovarian cancer patients, the build up of fluid in the peritoneal cavity leads to the production of protein and cell rich asciites. Physiological movement establishes ascitic currents in the peritoneal cavity. The ascitic currents represent external flow which plays an important role in disseminating and modulating the biology of the ovarian cancer. Furthermore, the interstitial flow build-up inside tumor nodules establishes outward fluidic streams. The fluidic internal and external streams play an important role in drug delivery, which is also affected by permeability, an important physical property of the tumor. Permeability defines the flow dynamics over and through the tumor nodule, influencing therapy. The permeability of the tumor also affects the magnitude and distribution of fluidic shear stress experienced by the nodule. We propose to use experimental optical observations and mathematical descriptions of flow and mass transport for estimation of (i) the flow pattern around and through 3D porous cancer nodule surrogate, and (ii) the surrogate permeability. The permeability is estimated using an optimization technique in which the permeability value is iteratively modified to minimize the difference between the numerical solution of the mathematical model and the optical measurements. This algorithm is robust to discrepancy between the mathematical model and the experimental measurements. In this presentation, we show the feasibility of using particle image velocimetry (PIV) and confocal microscopy for estimating the permeability of a tumor surrogate by the optimization technique. Results suggest that the developed optimization toolbox can be used to estimate the tumor permeability in live 3D models of ovarian cancer.

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Sepideh Afshar, Imran Rizvi, and Walfre Franco "Estimation of permeability from optical observations in a model system of 3D ovarian cancer nodules subjected to fluidic shear stress (Conference Presentation)", Proc. SPIE 10875, Microfluidics, BioMEMS, and Medical Microsystems XVII, 1087513 (4 March 2019); https://doi.org/10.1117/12.2510089

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KEYWORDS

3D modeling

Ovarian cancer

Tumors

Tumor growth modeling

Systems modeling

Fluid dynamics

3D metrology

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