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• W2912162594 abstract "Convection-enhanced delivery (CED) is an investigational therapy developed to circumvent the limitations of drug delivery to the brain. Catheters are used in CED to locally infuse therapeutic agents into brain tissue. CED has demonstrated clinical utility for treatment of malignant brain tumors; however, CED has been limited by lack of CED-specific catheters. Therefore, we developed a multiport, arborizing catheter to maximize drug distribution for CED. Using a multiphasic finite element (FE) framework, we parametrically determined the influence of design variables of the catheter on the dispersal volume of the infusion. We predicted dispersal volume of a solute infused in a permeable hyperelastic solid matrix, as a function of separation distance (ranging from 0.5 to 2.0 cm) of imbedded infusion cavities that represented individual ports in a multiport catheter. To validate the model, we compared FE solutions of pressure-controlled infusions to experimental data of indigo carmine dye infused in agarose tissue phantoms. The Tc50, defined as the infusion time required for the normalized solute concentration between two sources to equal 50% of the prescribed concentration, was determined for simulations with infusion pressures ranging from 1 to 4 kPa. In our validated model, we demonstrate that multiple ports increase dispersal volume with increasing port distance but are associated with a significant increase in infusion time. Tc50 increases approximately tenfold when doubling the port distance. Increasing the infusion flow rate (from 0.7 μL/min to 8.48 μL/min) can mitigate the increased infusion time. In conclusion, a compromise of port distance and flow rate could improve infusion duration and dispersal volume." @default.
• W2912162594 created "2019-02-21" @default.
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• W2912162594 date "2019-04-01" @default.
• W2912162594 modified "2023-10-16" @default.
• W2912162594 title "Parametric Study of the Design Variables of an Arborizing Catheter on Dispersal Volume Using a Biphasic Computational Model" @default.
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• W2912162594 doi "https://doi.org/10.1115/1.4042874" @default.
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• W2912162594 hasPublicationYear "2019" @default.
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