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A new surgical path planning framework for neurosurgery.

Meltem Kurt Pehlivanoğlu¹, Eren Cem Ay¹, Ayşe Gül Eker¹

¹Department of Computer Engineering, Kocaeli University, Kocaeli, Turkey.

The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS

|September 29, 2023

Summary

This study introduces a novel surgical path planning framework for neurosurgery, enabling instrument-independent, patient-specific curvilinear path generation by integrating brain atlases and tract imaging. The framework successfully identified standard surgical pathways, demonstrating its potential for complex procedures.

Keywords:

A*Dijkstra brain atlases neurosurgery surgical path planning

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Area of Science:

Neurosurgery
Medical Image Analysis
Computational Anatomy

Background:

Existing path-finding algorithms often overlook comprehensive brain structures and instrument dependencies.
Curvilinear path planning in neurosurgery is complex due to numerous surgical and physiological constraints.
There is a need for methods that integrate brain atlases, white matter tracts, and segmented regions for precise surgical planning.

Purpose of the Study:

To develop an instrument-independent surgical path planning framework for neurosurgery.
To enable the generation of patient-specific, curvilinear surgical pathways.
To consider the entire brain structure, including tracts and segmented areas, in path planning.

Main Methods:

Integration of atlas-based segmentation with path-finding algorithms (Dijkstra, A*).
Incorporation of risk scores for sensitive brain areas, assessed by surgeons (0-10 scale).
Utilized tract image processing techniques: fractional anisotropy (FA), relative anisotropy (RA), spherical measure (SM), and linear measure (LM).

Main Results:

First framework to combine white matter tracts and atlas-based segmentation for surgical path planning.
Dynamic framework structure allows for addition of various path-finding algorithms and pathway widths.
Generated surgical paths in NRRD format for compatibility with third-party software.
Surgeon validation confirmed the framework's ability to identify standard surgical pathways (e.g., anterior transsylvian, trans sulcal).

Conclusions:

The proposed framework successfully generates multiple potential surgical pathways evaluated by surgeons.
The framework identifies real-world surgical pathways, validating its clinical relevance.
Future enhancements include incorporating parameters like operation time and complication rates for complex surgical conditions.