Young, otherwise healthy amputees form a small but growing population of patients, many of them the casualties of combat, and there is a persistent need in this group for improvements in the fixation of prosthetic limbs. A recent approach to this problem is to embed metallic posts into the remnant bone of the limb and thus provide a stable fixation point that reduces the abrasion and contact wounds of the typical stump-and-socket prosthetic fixation. One drawback to this approach is the long (many months) healing time required for full embedding of the implant, a process we hope to accelerate through the application of an electric field across the interface from the bone to the implant. It is known that electric fields facilitate bone growth so that attachment of external stimulating electrodes could accelerate bone/implant attachment and reduce healing time. However, this is a novel application of the concept with no previous data to help determine optimal electrode location or applied field values. We are using patient specific, image based modeling to create simulations of the limb, the implant, and the spatial distributions of electric fields that result from application of surface electrodes.

Implantable Cardiac Defibrillators (ICDs) save the lives of patients with unstable heart rhythms and 100,000 patients receive these devices per year in the US. Their use in children is less frequent and less standardized than in adults so that determining efficient electrode placement is challenging and uncertain. We are collaborating with J. Triedman, M.D. at Children's Hospital Boston and M. Jolley, M.D. at Stanford University to develop interactive finite element (FEM) computational models to test electrode locations for their effectiveness in defibrillation in children. The models come from CT or MRI scans segmented into tissue types and then meshed for FEM. The system also includes a library of realistically shaped ICD case and wire electrodes and an interactive interface allows the user to easily place and move the electrodes in the model to evaluate different implantation locations. To date we have fully segmented three CT scans, from 2, 10, and 27 year-old subjects, and have created a database of approximately 100 suitable electrode locations per model, which we are testing for bioelectric field strength and homogeneity. Initial findings have included evaluating the effectiveness of standard locations in adults and novel locations in children.