Modelling convection-enhanced delivery in normal and oedematous brain

Abstract

Convection-enhanced delivery (CED) could have clinical applications in the delivery of neuroprotective agents in brain injury states, such as ischaemic stroke. For CED to be safe and effective, a physician must have accurate knowledge of how concentration distributions will be affected by catheter location, flow rate and other similar parameters. In most clinical applications of CED, brain microstructures will be altered by pathological injury processes. Ischaemic stroke and other acute brain injury states are complicated by formation of cytotoxic oedema, in which cellular swelling decreases the fractional volume of the extracellular space (ECS). Such changes would be expected to significantly alter the distribution of neuroprotective agents delivered by CED. Quantitative characterization of these changes will help confirm this prediction and assist in efforts to model the distribution of therapeutic agents. Three-dimensional computational models based on a Nodal Point Integration (NPI) scheme were developed to model infusions in normal brain and brain with cytotoxic oedema. These models were compared to experimental data in which CED was studied in normal brain and in a middle cerebral artery (MCA) occlusion model of cytotoxic oedema. The computational models predicted concentration distributions with reasonable accuracy.

• Cerebral infarction
• convection-enhanced delivery
• cytotoxic oedema
• finite element model
• Gd-DTPA
• intraparenchymal infusion
• rat brain
• stroke

Acknowledgements

PJH was supported by a Ruth L. Kirschstein National Research Service Award (NRSA) Predoctoral Fellowship (1 F31 NS048813-01). This work was supported in part by the Hord and Cullather funds of the Medical College of Virginia Foundation. The work at the University of Virginia was supported in part by the Kopf Family Foundation, Inc. The authors would like to acknowledge several useful technical discussions with our collaborator, Raghu Raghavan, PhD (Therataxis, LLC). Additionally, the authors acknowledge the software support and technical advice of Akshai Runchal, PhD (ACRi CFD).