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Model-based correction for brain shift in deep brain stimulation burr hole procedures: a comparison using interventional magnetic resonance imaging
Author(s): Ma Luo; Saramati Narasimhan; Alastair J. Martin; Paul S. Larson; Michael I. Miga
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Paper Abstract

Deep brain stimulation (DBS) is an effective treatment for movement disorders, e.g. Parkinson’s disease. The quality of DBS treatment is dependent on the implantation accuracy of DBS electrode leads into target structures. However, brain shift during burr hole procedures has been documented and hypothesized to negatively impact treatment quality. Several approaches have been proposed to compensate for brain shift in DBS, namely microelectrode recording (MER) and interventional magnetic resonance (iMR) imaging. Though both demonstrate benefits in guiding accurate electrode placement, they suffer drawbacks such as prolonged procedures and in the latter, cost considerations. Hence, we are exploring a model-based brain shift compensation strategy in DBS to improve targeting accuracy for surgical navigation. Our method is a deformation-atlas-based approach, i.e. potential intraoperative deformations are pre-computed via biomechanical model under varying conditions, combined with an inverse problem driven by sparse intraoperative data for estimating volumetric brain deformations. In this preliminary feasibility study, we examine our model’s ability to predict brain shift in DBS by comparing with iMR in one patient. The evaluation includes: (1) a subsurface deformation comparison where subsurface shifts measured by iMR are compared to model-predicted counterparts; (2) a second comparison at surgical targets where the atlas-method is compared to deformations measured by non-rigid image-to-image registration using preoperative image and iMR. For the former, the model reduces alignment error from 8.6 ± 1.4 to 3.6 ± 0.8 mm, representing ~58.6% correction. For the latter, model estimated brain shifts at surgical targets are 2.4 and 0.6 mm, consistent with clinical observations.

Paper Details

Date Published: 12 March 2018
PDF: 10 pages
Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105760P (12 March 2018); doi: 10.1117/12.2293386
Show Author Affiliations
Ma Luo, Vanderbilt Univ. (United States)
Saramati Narasimhan, Vanderbilt Univ. (United States)
Alastair J. Martin, Univ. of California, San Francisco (United States)
Paul S. Larson, Univ. of California, San Francisco (United States)
Michael I. Miga, Vanderbilt Univ. (United States)


Published in SPIE Proceedings Vol. 10576:
Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Robert J. Webster, Editor(s)

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