We propose a framework for electromagnetic (EM) simulation of deep brain stimulation (DBS) patients in radiofrequency (RF) coils. We generated a model of a DBS patient using post-operative head and neck computed tomography (CT) images stitched together into a 'virtual CT' image covering the entire length of the implant. The body was modeled as homogeneous. The implant path extracted from the CT data contained self-intersections, which we corrected automatically using an optimization procedure. Using the CT-derived DBS path, we built a model of the implant including electrodes, helicoidal internal conductor wires, loops, extension cables, and the implanted pulse generator. We also built four simplified models with straight wires, no extension cables and no loops to assess the impact of these simplifications on safety predictions. We simulated EM fields induced by the RF birdcage body coil in the body model, including at the DBS lead tip at both 1.5 Tesla (64 MHz) and 3 Tesla (123 MHz). We also assessed the robustness of our simulation results by systematically varying the EM properties of the body model and the position and length of the DBS implant (sensitivity analysis). The topology correction algorithm corrected all self-intersection and curvature violations of the initial path while introducing minimal deformations (open-source code available at http://ptx.martinos.org/index.php/Main-Page). The unaveraged lead-tip peak SAR predicted by the five DBS models (0.1 mm resolution grid) ranged from 12.8 kW kg-1 (full model, helicoidal conductors) to 43.6 kW kg-1 (no loops, straight conductors) at 1.5 T (3.4-fold variation) and 18.6 kW kg-1 (full model, straight conductors) to 73.8 kW kg-1 (no loops, straight conductors) at 3 T (4.0-fold variation). At 1.5 T and 3 T, the variability of lead-tip peak SAR with respect to the conductivity ranged between 18% and 30%. Variability with respect to the position and length of the DBS implant ranged between 9.5% and 27.6%.
Bibliographical noteFunding Information:
This work was supported by NIH grants R00EB019482 (Guerin),P41EB015896 (Guerin,Wald),R03MH111320 (Widge), R21MH109722 (Widge), UH3NS100548 (Widge, Dougherty), R01MH111872 (Widge), R01EB006847 (Guerin, Wald) as well as grants from the Brain and Behavior Research Foundation (Widge), Harvard Brain Science Initiative (Widge),MIT-MGH Strategic Initiative (Widge),American Brain Foundation/ American Academy of Neurology (Herrington) and the Bachman–Strauss Dystonia and Parkinson Foundation (Herrington).
- RF safety
- deep brain stimulation
- electromagnetic modeling
- magnetic resonance imaging