GPU-based real-time approximation of the ablation zone for radiofrequency ablation

Area of Science:

• Medical imaging
• Computational modeling
• Minimally invasive surgery

Background:

• Percutaneous radiofrequency ablation (RFA) is a standard treatment for liver tumors.
• Accurate planning of applicator placement is crucial for complete tumor destruction but requires significant expertise.
• Existing methods may lack real-time feedback for optimizing treatment parameters.

Purpose of the Study:

• To develop a fast, GPU-based system for real-time approximation of the radiofrequency ablation (RFA) zone.
• To incorporate the heat-sink effect of liver blood vessels into the ablation zone prediction.
• To assist physicians in interactive planning and optimization of RFA applicator placement for liver tumors.

Main Methods:

• Utilized weighted distance fields derived from numerical simulations for rapid ablation zone estimation.
• Incorporated a preprocessed thermal equilibrium model to estimate the cooling effect of blood flow.
• Implemented a modular shader framework on a GPU for real-time calculation and visualization of the ablation zone.
• Integrated the system into a software prototype for interactive RFA planning.

Main Results:

• Achieved fast, GPU-based real-time approximation of the RFA ablation zone.
• Successfully integrated the cooling effect of liver vessels into the ablation zone model.
• Demonstrated real-time visualization capabilities in slice views and volume rendering.
• Developed a functional software prototype for interactive RFA therapy planning.

Conclusions:

• The developed GPU-based method provides a fast and accurate approximation of the RFA ablation zone, including vascular cooling effects.
• The real-time visualization facilitates interactive evaluation and optimization of applicator placement.
• This tool can significantly improve the precision and effectiveness of RFA treatment for liver tumors.