Literature DB >> 32078527

Accounting for Deformation in Deep Brain Stimulation Surgery With Models: Comparison to Interventional Magnetic Resonance Imaging.

Ma Luo, Paul S Larson, Alastair J Martin, Michael I Miga.   

Abstract

The efficacy of deep brain stimulation (DBS) depends on electrode placement accuracy, which can be jeopardized by brain shift due to burr hole and dura opening during surgery. Brain shift violates assumed rigid alignment between preoperative image and intraoperative anatomy, negatively impacting therapy.
OBJECTIVE: This study presents a deformation-atlas biomechanical model-based approach to address shift.
METHODS: Six patients, who underwent interventional magnetic resonance (iMR) image-guided DBS burr hole surgery, were studied. A patient-specific model was employed under varying surgical conditions, generating a collection of possible intraoperative shift estimations or a 'deformation atlas.' An inverse problem was driven by sparse measurements derived from iMR to determine an optimal fit of solutions of the atlas. This fit was then used to obtain a volumetric deformation field, which was utilized to update preoperative MR and estimate shift at surgical target region localized on iMR. Model performance was examined by quantitatively comparing intraoperative subsurface measurements to their model-predicted counterparts, and qualitatively comparing iMR, preoperative MR, and model updated MR. A nonrigid image registration was introduced as a comparator.
RESULTS: Model-based approach reduced general parenchyma shift from 8.2 ± 2.2 to 2.7 ± 1.1 mm (∼66.8% correction), and produced updated MR with better agreement to iMR than that of preoperative MR. The average model estimated shift at target region was 1.2 mm.
CONCLUSIONS: This study demonstrates the feasibility of a model-based shift correction strategy in DBS surgery with only sparse data. SIGNIFICANCE: The developed strategy has the potential to complement and/or enhance current clinical approaches in addressing shift.

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Year:  2020        PMID: 32078527      PMCID: PMC9476051          DOI: 10.1109/TBME.2020.2974102

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.756


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