SlicerCBM

SlicerCBM predicts intra-operative brain deformations (brain shift) from pre-operative MRI using biomechanical modeling to support neurosurgical target localization.

Key Features:

• Integration with 3D Slicer: Integrates with the 3D Slicer open-source platform and additional libraries to perform medical image–based biomechanical modeling.
• Meshless Total Lagrangian Explicit Dynamics (MTLED): Uses the MTLED algorithm to compute soft tissue deformations without relying on a predefined mesh structure.
• Automated MRI-to-prediction workflow: Automates the process from pre-operative MRI input to generation of predicted intra-operative MRI outputs via biomechanical simulation.
• Application scenarios: Applied to predict brain shift in craniotomy, tumor resection, and electrode placement contexts.
• Evaluation and validation: Supports qualitative comparison with intra-operative MRI and quantitative validation using Hausdorff distances between predicted and actual ventricle surfaces.

Scientific Applications:

• Neurosurgical target localization: Predicts brain shift to adjust intra-operative localization of surgical targets.
• Craniotomy planning: Estimates deformation during craniotomy to inform surgical strategy.
• Tumor resection guidance: Predicts tissue displacement to support accurate tumor resection.
• Electrode placement planning: Models deformation associated with electrode placement to improve placement accuracy.

Methodology:

Constructs a biomechanical brain model from pre-operative MRI (≈3 minutes), computes tissue deformations using the MTLED algorithm (≈13–23 minutes), and evaluates predictions via qualitative comparison to intra-operative MRI and quantitative Hausdorff distance calculations between predicted and actual ventricle surfaces.