Three-dimensional nonlinear finite element model to estimate backflow during flow-controlled infusions into the brain

Author:

Orozco Gustavo A1ORCID,Smith Joshua H2,García José J3

Affiliation:

1. Department of Applied Physics, University of Eastern Finland, Kuopio, Finland

2. Department of Mechanical Engineering, Lafayette College, Easton, PA, USA

3. Escuela de Ingeniería Civil y Geomática, Universidad del Valle, Cali, Colombia

Abstract

Convection-enhanced delivery is a technique to bypass the blood–brain barrier and deliver therapeutic drugs into the brain tissue. However, animal investigations and preliminary clinical trials have reported reduced efficacy to transport the infused drug in specific zones, attributed mainly to backflow, in which an annular gap is formed outside the catheter and the fluid preferentially flows toward the surface of the brain rather than through the tissue in front of the cannula tip. In this study, a three-dimensional human brain finite element model of backflow was developed to study the influence of anatomical structures during flow-controlled infusions. Predictions of backflow length were compared under the influence of ventricular pressure and the distance between the cannula and the ventricles. Simulations with zero relative ventricle pressure displayed similar backflow length predictions for larger cannula-ventricle distances. In addition, infusions near the ventricles revealed smaller backflow length and the liquid was observed to escape to the longitudinal fissure and ventricular cavities. Simulations with larger cannula-ventricle distances and nonzero relative ventricular pressure showed an increase of fluid flow through the tissue and away from the ventricles. These results reveal the importance of considering both the subject-specific anatomical details and the nonlinear effects in models focused on analyzing current and potential treatment options associated with convection-enhanced delivery optimization for future clinical trials.

Publisher

SAGE Publications

Subject

Mechanical Engineering,General Medicine

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