Literature DB >> 33426993

Imaging-based characterization of convective tissue properties.

D Fuentes1,2, E Thompson1, M Jacobsen1, A Colleen Crouch3, R R Layman1, B Riviere2, E Cressman3.   

Abstract

Convective transport is an important phenomenon for nanomedicine delivery. We present an imaging-based approach to recover tissue properties that are significant in the accumulation of nanoparticles delivered via systemic methods. The classical pharmacokinetic analysis develops governing equations for the particle transport from a first principle mass balance. Fundamentally, the governing equations for compartmental mass balance represent a spatially invariant mass transport between compartments and do not capture spatially variant convection phenomena. Further, the parameters recovered from this approach do not necessarily have direct meaning with respect to the governing equations for convective transport. In our approach, a framework is presented for directly measuring permeability in the sense of Darcy flow through porous tissue. Measurements from our approach are compared to an extended Tofts model as a control. We demonstrate that a pixel-wise iterative clustering algorithm may be applied to reduce the parameter space of the measurements. We show that measurements obtained from our approach are correlated with measurements obtained from the extended Tofts model control. These correlations demonstrate that the proposed approach contains similar information to an established compartmental model and may be useful in providing an alternative theoretical framework for parameterizing mathematical models for treatment planning and diagnostic studies involving nanomedicine where convection dominated effects are important.

Keywords:  Modeling (i.e., heat transfer, ultrasound, EM, integrated, treatment planning); mass transport; mixture theory; Darcy law

Mesh:

Year:  2020        PMID: 33426993      PMCID: PMC7983068          DOI: 10.1080/02656736.2020.1845403

Source DB:  PubMed          Journal:  Int J Hyperthermia        ISSN: 0265-6736            Impact factor:   3.914


  41 in total

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Journal:  ACS Nano       Date:  2020-04-14       Impact factor: 15.881

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10.  Nanoparticle interactions with immune cells dominate tumor retention and induce T cell-mediated tumor suppression in models of breast cancer.

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Journal:  Sci Adv       Date:  2020-03-25       Impact factor: 14.136

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