| description abstract | Implementation of a novel direct tumortargeting technique requires a computer modeling stage to generate particle release maps (PRMs) which allow for optimal catheter positioning and selection of best injection intervals for drugparticles. This simulation task for a patientspecific PRM may require excessive computational resources and a relatively long turnaround time for a fully transient analysis. Hence, steadystate conditions were sought which generates PRMs equivalent to the pulsatile arterial flow environment. Fluidparticle transport in a representative hepatic artery system was simulated under fully transient and steadystate flow conditions and their corresponding PRMs were analyzed and compared. Comparisons of the transient PRMs from ten equal intervals of the cardiac pulse revealed that the diastolic phase produced relatively constant PRMs due to its semisteady flow conditions. Furthermore, steadystate PRMs, which best matched the transient particle release maps, were found for each interval and over the entire cardiac pulse. From these comparisons, the flow rate and outlet pressure differences proved to be important parameters for estimating the PRMs. The computational times of the fully transient and steady simulations differed greatly, i.e., about 10 days versus 0.5 to 1 h, respectively. The timeaveraged scenario may provide the best steady conditions for estimating the transient particle release maps. However, given the considerable changes in the PRMs due to the accelerating and decelerating phases of the cardiac cycle, it may be better to model several steady scenarios, which encompass the wide range of flows and pressures experienced by the arterial system in order to observe how the PRMs may change throughout the pulse. While adding more computation time, this method is still significantly faster than running the full transient case. Finally, while the best steady PRMs provide a qualitative guide for best catheter placement, the final injection position could be adjusted in vivo using biodegradable mockspheres to ensure that patientspecific optimal tumortargeting is achieved. In general, the methodology described could generate computationally very efficient and sufficiently accurate solutions for the transient fluidparticle dynamics problem. However, future work should test this methodology in patientspecific geometries subject to various flow waveforms. | |
