Numerical study of intrathecal drug delivery to a permeable spinal cord: effect of catheter position and angle.

Intrathecal delivery is a procedure involving the release of therapeutic agents into the cerebrospinal fluid (CSF) hrough a catheter. It holds promise for treating high-impact central nervous system pathologies, for which systemic administration routes are ineffective. In this study we introduce a numerical model able to simultaneously account for solute transport in the fluid and in the spinal cord. Using a Discontinuous Galerkin method and a three-dimensional patient-specific geometry, we studied the effect of catheter position and angle on local spinal cord drug concentration. We considered twenty cardiac cycles to limit the computational cost of our approach, which resolves the physics both in space and time. We used clinically representative data for the drug injection speed and dose rate, and scaled drug diffusion/penetration properties to obtain observable effects during the considered simulation time. Based on our limited set of working parameters, lateral injection perpendicular to the cord turned out to be more effective than other configurations. Even if the adopted scaling does not allow for a direct clinical translation (a wider parametric assessment of the importance of CSF flow, geometry and diffusion properties is needed), it did not weaken our numerical approach, which can be used to systematically investigate multiple catheter, geometry and fluid/tissue properties configurations, thus paving the way for therapy control.

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.

On the preliminary design of hyperthermia treatments based on infusion and heating of magnetic nanofluids.

We study a magnetic-nanoparticle-mediated hyperthermia treatment by considering both the nanofluid infusion and the subsequent thermal activation of the infused nanoparticles. Our study aims at providing a quantitative framework, which is currently missing, for the design of hyperthermia treatments. In more detail, we consider a heterogeneous spherical tumor, and we obtain a simplified analytical expression for the nanoparticles concentration profile during the infusion. We then exploit such an expression in order to compute the steady-state temperature profile achieved through the heating step. Despite the simplifications introduced to enable the analytical derivations, we account for many physically relevant aspects including tissue heterogeneity, poroelasticity, blood perfusion, and nanoparticles absorption onto tissue. Moreover, our approach permits to elucidate the effects on the final temperature profile of the following control parameters: infusion duration and flow rate, nanoparticles concentration in the nanofluid, magnetic field intensity and frequency. We present illustrative numerical results, based on parameters values taken from experimental studies, which are consistent with previous numerical investigations and current hyperthermia approaches. In particular, we obtain optimal working curves which could be effectively used for planning real procedures. While not laying any claims of generality, this work takes a preliminary yet quantitative step toward the design of hyperthermia treatments.

Model-based control of plasma glycemia: Tests on populations of virtual patients.

Closed-loop devices delivering medical treatments in an automatic fashion clearly require a thorough preliminary phase according to which the proposed control law is tested and validated as realistically as possible, before arranging in vivo experiments in a clinical setting. The present note develops a virtual environment aiming to validate a recently proposed model-based glucose control law on a solid simulation framework. From a theoretical viewpoint, the artificial pancreas has been designed by suitably exploiting a minimal set of delay differential equations modeling the glucose-insulin regulatory system; on the other hand, the validation platform makes use of a different, multi-compartmental model to build up a population of virtual patients. Simulations are carried out by properly addressing the available technological limits and the unavoidable uncertainties in real-time continuous glucose sensors as well as possible malfunctioning on the insulin delivery devices. The results show the robustness of the proposed control law that turns out to be efficient and extremely safe on a heterogenous population of virtual patients.