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3D XFEM-based modeling of retraction for preoperative image update
Lara M Vigneron1, Simon K Warfield, Pierre A Robe
1Department of Electrical Engineering and Computer Science, University of Liège, Liège, Belgium. lara.vigneron@gmail.com
Summary
This study introduces a novel 3D nonrigid registration technique to accurately track brain deformation during neurosurgery, improving intraoperative navigation and MRI alignment.
Area of Science:
- Neurosurgery
- Medical Imaging
- Biomechanical Modeling
Background:
- Intraoperative navigation in neurosurgery is crucial for patient outcomes.
- Current systems struggle to accurately model intraoperative brain deformation, particularly that caused by retraction.
- Existing research primarily addresses brain shift, overlooking retraction-induced deformation.
Purpose of the Study:
- To develop and validate a novel system for accurately accounting for brain deformation caused by retraction during neurosurgery.
- To enhance the precision of intraoperative navigation and guidance systems.
- To improve the alignment of intraoperative magnetic resonance imaging (MRI).
Main Methods:
- A 3D nonrigid registration technique utilizing a biomechanical model.
- Tracking deformations of key surfaces (brain boundary, retraction site) between intraoperative images.
- Employing the eXtended Finite Element Method (XFEM) to manage tissue discontinuity without remeshing.
Main Results:
- The proposed system effectively models brain deformation due to gravity and retractor deployment.
- The eXtended Finite Element Method (XFEM) successfully handles tissue discontinuity.
- Significant improvement in the alignment accuracy of intraoperative MRI was demonstrated.
Conclusions:
- The developed biomechanical model and XFEM-based registration technique offer a significant advancement in neurosurgical navigation.
- Accurate modeling of retraction-induced brain deformation enhances intraoperative guidance.
- This approach promises to improve surgical precision and patient outcomes in neurosurgery.
