Backflow length predictions during flow-controlled infusions using a nonlinear biphasic finite element model

A Biphasic Fluid-Structure Interaction Model of Backflow During Infusion Into Agarose Gel

The efficacy of convection-enhanced delivery as a technique to treat disorders of the central nervous system is limited by backflow, in which the infused fluid flows backward along surface of the catheter rather than toward the targeted area. In order to improve treatment protocols, finite element models of backflow have been developed to understand the underlying physics. García et al. (2013, "Description and Validation of a Finite Element Model of Backflow During Infusion Into a Brain Tissue Phantom," ASME J. Comput. Nonlinear Dyn., 8(1), p. 011017) presented a finite element model that accounted for the flow in the annular gap that develops between the tissue and the outer surface of the catheter by using a layer of biphasic elements with a formula for the axial hydraulic conductivity to represent annular Poiseuille flow. In this study, we present a generalization of that model using fluid-FSI and biphasic-FSI elements that are recently available in febio. We demonstrate that our model of a 0.98 mm radius catheter is able to reproduce experimental backflow lengths and maximum fluid pressures for infusions into a brain tissue surrogate and that it agrees well with the previous model by García et al. (2013, "Description and Validation of a Finite Element Model of Backflow During Infusion Into a Brain Tissue Phantom," ASME J. Comput. Nonlinear Dyn., 8(1), p. 011017). The model predicts that the backflow length and the total amount of flow into the hemispherical region forward of the catheter tip is comparable for two different catheter sizes, albeit at a higher fluid pressure for the smaller catheter. This biphasic-FSI model has the potential to be extended to a stepped catheter geometry, which has been shown in experiments to be successful in controlling backflow.

Constant Pressure Convection-Enhanced Delivery Increases Volume Dispersed With Catheter Movement in Agarose

Convection-enhanced delivery (CED) has been extensively studied for drug delivery to the brain due to its inherent ability to bypass the blood-brain barrier. Unfortunately, CED has also been shown to inadequately distribute therapeutic agents over a large enough targeted tissue volume to be clinically beneficial. In this study, we explore the use of constant pressure infusions in addition to controlled catheter movement as a means to increase volume dispersed (Vd) in an agarose gel brain tissue phantom. Constant flow rate and constant pressure infusions were conducted with a stationary catheter, a catheter retracting at a rate of 0.25 mm/min, and a catheter retracting at a rate of 0.5 mm/min. The 0.25 mm/min and 0.5 mm/min retracting constant pressure catheters resulted in significantly larger Vd compared to any other group, with a 105% increase and a 155% increase compared to the stationary constant flow rate catheter, respectively. These same constant pressure retracting infusions resulted in a 42% and 45% increase in Vd compared to their constant flow rate counterparts. Using constant pressure infusions coupled with controlled catheter movement appears to have a beneficial effect on Vd in agarose gel. Furthermore, constant pressure infusions reveal the fundamental limitation of flow-driven infusions in both controlled catheter movement protocols as well as in stationary protocols where maximum infusion volume can never be reliably obtained.

Convection-enhanced delivery with controlled catheter movement: A parametric finite element analysis

Convection-enhanced delivery (CED) is an investigational method for delivering therapeutics directly to the brain for the treatment of glioblastoma. However, it has not become a common clinical therapy due to an inability of CED treatments to deliver therapeutics in a large enough tissue volume to fully saturate the target region. We have recently shown that the combination of controlled catheter movement and constant pressure infusions can be used to significantly increase volume dispersed (Vd ) in an agarose gel brain tissue phantom. In the present study, we develop a computational model to predict Vd achieved by various retraction rates with both constant pressure and constant flow rate infusions. An increase in Vd is achieved with any movement rate, but increase in Vd between successive movement rates drops off at rates above 0.3-0.35 mm/min. Finally, we found that infusions with retraction result in a more even distribution in concentration level compared to the stationary catheter, suggesting a potential increased ability for moving catheters to have a therapeutic impact regardless of the required therapeutic concentration level.

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

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.

Convection enhanced delivery of liposome encapsulated doxorubicin for brain tumour therapy

Convection enhanced delivery is promising to overcome the blood brain barrier. However, the treatment is less efficient in clinic due to the rapid elimination of small molecular drugs in brain tumours. In this study, numerical simulation is applied to investigate the convection enhanced delivery of liposome encapsulated doxorubicin under various conditions, based on a 3-D brain tumour model that is reconstructed from magnetic resonance images. Treatment efficacy is evaluated in terms of the tumour volume where the free doxorubicin concentration is above LD90. Simulation results denote that intracerebral infusion is effective in increasing the interstitial fluid velocity and inhibiting the fluid leakage from blood around the infusion site. Comparisons with direct doxorubicin infusion demonstrate the advantages of liposomes in enhancing the doxorubicin accumulation and penetration in the brain tumour. Delivery outcomes are determined by both the intratumoural environment and properties of therapeutic agents. The treatment efficacy can be improved by either increasing the liposome solution concentration and infusion rate, administrating liposomes in the tumour with normalised microvasculature density, or using liposomes with low vascular permeability. The delivery is less sensitive to liposome diffusivity in the examined range (E-11~E-7 cm²/s) as convective transport is dominative in determining the liposome migration. Drug release rate is able to be optimised by keeping a trade-off between enhancing the drug penetration and providing sufficient free doxorubicin for effective cell killing. Results from this study can be used to improve the regimen of CED treatments.

Convection enhanced delivery of chemotherapeutic drugs into brain tumour

Convection enhanced delivery (CED) of chemotherapeutic drugs can successfully bypass the blood-brain barrier (BBB). However, the treatment efficacy is significantly variable in clinic owing to the absence of proper drugs and the lack of understanding on the local drug transport. In this study, mathematical modelling is employed to investigate the suitability of six chemotherapeutic drugs from the perspective of intratumoural transport, including fluorouracil, carmustine, cisplatin, methotrexate, doxorubicin and paclitaxel. The convection/diffusion/reaction model coupled with Darcy's law is applied to a 3-D realistic brain tumour model that is extracted from magnetic resonance (MR) images. The modelling demonstrates the advantages of CED in enhancing the convective flow of interstitial fluid and reducing the drug concentration dilution caused by the fluid loss from blood stream in the tumour region around the infusion site. The delivery outcomes of the drug in CED treatments are strongly dependent on its physicochemical properties. Convection is more effective in determining the transport of paclitaxel and methotrexate in brain tumour. Paclitaxel exhibits its superiority in drug penetration and accumulation, resulting in the largest effective delivery volume as compared to the other studied drugs. Nanocarrier and diagnostic ultrasound are able to enhance the drug penetration for achieving improved delivery outcomes. Results obtained in this study can serve as a guide for optimising CED treatment regimens.

An analytical model for nanoparticles concentration resulting from infusion into poroelastic brain tissue

We consider the infusion of a diluted suspension of nanoparticles (NPs) into poroelastic brain tissue, in view of relevant biomedical applications such as intratumoral thermotherapy. Indeed, the high impact of the related pathologies motivates the development of advanced therapeutic approaches, whose design also benefits from theoretical models. This study provides an analytical expression for the time-dependent NPs concentration during the infusion into poroelastic brain tissue, which also accounts for particle binding onto cells (by recalling relevant results from the colloid filtration theory). Our model is computationally inexpensive and, compared to fully numerical approaches, permits to explicitly elucidate the role of the involved physical aspects (tissue poroelasticity, infusion parameters, NPs physico-chemical properties, NP-tissue interactions underlying binding). We also present illustrative results based on parameters taken from the literature, by considering clinically relevant ranges for the infusion parameters. Moreover, we thoroughly assess the model working assumptions besides discussing its limitations. While not laying any claims of generality, our model can be used to support the development of more ambitious numerical approaches, towards the preliminary design of novel therapies based on NPs infusion into brain tissue.