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An Integrated Multi-physics Finite Element Modeling Framework for Deep Brain Stimulation: Preliminary Study on Impact of Brain Shift on Neuronal Pathways

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Book cover Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 (MICCAI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11768))

Abstract

Deep brain stimulation (DBS) is an effective therapy for movement disorders. The efficacy of DBS depends on electrode placement accuracy and programming parameter optimization to modulate desired neuron groups and pathways. Compounding the challenge of surgical targeting and therapy delivery is brain shift during DBS burr hole surgery. Brain shift introduces potentially significant misalignment between intraoperative anatomy and preoperative imaging data used for surgical planning and targeting. Brain shift may also impact the volume of tissue activation (VTA) and consequently neuronal pathway recruitment for modulation. This work introduces an integrated framework of patient specific biomechanical and bioelectric models to account for brain shift and examines its impact on DBS delivery. Specifically, the biomechanical model was employed to predict brain shift via an inverse problem approach, which was driven by sparse data derived from interventional magnetic resonance (iMR) imaging data. A bioelectric model consisting of standard conductive physics was employed to predict electric potential maps in the presence of the deformed patient anatomy. The electrode leads for creating the potential maps were reconstructed from iMR visualized trajectory and a known lead model geometry. From the electric potential distribution, the VTA was estimated. In an effort to understand changes to neuronal pathway recruitment, the model displacement field was used to estimate shift impact on the VTA intraoperatively. Finally, VTAs in patient space with and without shift consideration were transformed to an atlas available via the Human Connectome Project where tractography was performed. This enabled the observation and comparison of neuronal pathway recruitment due to VTA distributions with and without shift considerations. Preliminary results using this framework in 2 patients indicate that brain shift impacts the extent, number, and volume of neuronal pathways affected by DBS. Hence consideration of brain shift in DBS burr hole surgery is desired to optimize outcome.

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Acknowledgements

The National Institutes of Health, R01NS049251.

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Correspondence to Ma Luo .

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Luo, M., Larson, P.S., Martin, A.J., Konrad, P.E., Miga, M.I. (2019). An Integrated Multi-physics Finite Element Modeling Framework for Deep Brain Stimulation: Preliminary Study on Impact of Brain Shift on Neuronal Pathways. In: Shen, D., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science(), vol 11768. Springer, Cham. https://doi.org/10.1007/978-3-030-32254-0_76

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  • DOI: https://doi.org/10.1007/978-3-030-32254-0_76

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-32254-0

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