A Computational Study of Blood Perfusion and Drug Transport in Tumors Based on an Embedded Multiscale Approach

Mechanical and Aerospace Engineering
Department Seminar Series

10/20 (Monday)   11:30 am – 12:30 pm     RH 202
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A Computational Study of Blood Perfusion and Drug Transport in Tumors Based on an Embedded Multiscale Approach

Paolo Zunino, Ph.D.
Assistant Professor
Department of Mechanical Engineering and Materials Science
University of Pittsburgh
Pittsburgh, PA

Reduced models of flow or mass transport in heterogeneous media are often adopted in the computational approach when the geometrical configuration of the system at hand is too complex. A paradigmatic example in this respect is blood flow through a network of capillaries surrounded by a porous interstitium. We numerically address this biological system by a computational model based on a multiscale resolution of embedded domains. Exploiting their large aspect ratio, we avoid resolving the complex 3D geometry of the submerged vessels by representing them with a 1D geometrical description of their centerline and the resulting network [1,2].

Cancer employs mass transport as a fundamental mechanism of coordination and communication and the physics of mass transport within body compartments and across biological barriers differentiates cancer from healthy tissues [3]. Mass transport is also at the basis of cancer pharmacological treatment Delivery of diagnostic and therapeutic agents differs dramatically between tumor and normal tissues. In contrast to healthy tissue, tumors exhibit interstitial hypertension, which is caused by the high permeability of tumor vessels in combination with the lack of functional lymphatic vessels in the tumor interstitial space.

The analysis of fluid and chemicals exchange in vascularized tumors is a relevant application of the model proposed here. We will use it to study fluid and mass exchange between the capillaries and the interstitial volume, as well as to compare different modalities to deliver chemotherapy drugs to the tumor mass, including using nanoparticles as delivery vectors [2,4].

[1] D'Angelo, C., Quarteroni, A. On the coupling of 1D and 3D diffusion-reaction equations. Application to tissue perfusion problems (2008) Mathematical Models and Methods in Applied Sciences, 18 (8), pp. 1481-1504.
[2] L. Cattaneo, P. Zunino, Computational models for fluid exchange between microcirculation and tissue interstitium, Networks and Heterogeneous Media, Vol. 9 (2014), No. 1, pp. 135159.
[3] Baxter, L.T., Jain, R.K. Transport of fluid and macromolecules in tumors. I. Role of interstitial pressure and convection (1989) Microvascular Research, 37 (1), pp. 77-104.
[4] L. Cattaneo, P. Zunino, A computational model of drug delivery through micro-circulation to compare different tumor treatments, Int. J. Numer. Meth. Biomed. Engng. (2014) DOI: 10.1002/cnm.2661.
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Biosketch

Assistant Professor, Mechanical Engineering, Ph.D in Applied Mathematics at the Ecole Polytecnique Fédérale de Lausanne, 2002. Dr. Zunino leads the Computational Biofluid Mechanics Laboratory active in the development of mathematical models and numerical approximation methods with application to engineering and life sciences. The current research projects, partially funded by NSF, NIH, DoE, include: the study of nonstandard finite element schemes for flow, transport and fluid-structure interaction; the application of such methods to forward and inverse problem formulations; computational modeling of multiphase flow and transport problems through heterogeneous media; computational modeling of microcirculation; computational modeling of fluid dynamics and drug release in biomedical devices. He has received the SIAM Outstanding Paper Prize, awarded by the Society for Industrial and Applied Mathematics, on July 2004. The prize, first awarded in 1999, is given to outstanding papers published in SIAM journals during the three years prior to the year of the award. He has co-authored the monograph “A Primer on PDEs, Models, Methods, Simulations” published by Springer on 2013.