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Abstract #0115

Prediction of subject-specific local SAR in patients with deep brain stimulation leads using artificial neural networks

Jasmine Vu1,2, Bach Nguyen2, Justin Baraboo1,2, Joshua Rosenow3, Julie Pilitsis4, and Laleh Golestanirad1,2
1Biomedical Engineering, Northwestern University, Chicago, IL, United States, 2Radiology, Northwestern University, Chicago, IL, United States, 3Northwestern Medicine, Chicago, IL, United States, 4Neurosurgery, Albany Medical Center, Albany, NY, United States

Patients with deep brain stimulation (DBS) implants can significantly benefit from MRI; however, their access is limited due to safety concerns associated with RF heating of implants. RF heating depends significantly on the trajectory of an implanted lead, but there is a lack of surgical guidelines about positioning the extracranial portion of the leads, resulting in substantial patient-to-patient variation in DBS lead trajectories. Thus, quick and reliable patient-specific assessment of RF heating is highly desirable. Here we present an artificial neural network (ANN) model that demonstrates great potential in predicting local SAR at the tips of the DBS leads.

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