An efficient thermal evolution model for cryoablation with arbitrary multi-cryoprobe configuration.

Area of Science:

• Biomedical Engineering
• Thermal Modeling
• Medical Physics

Background:

• Cryoablation is effective for tumor ablation by freezing target tissue.
• Accurate temperature prediction is vital for optimizing cryoablation procedures.
• Existing models may lack efficiency for complex cryoprobe configurations.

Purpose of the Study:

• To develop an efficient thermal model for predicting temperature evolution during cryoablation.
• To characterize the freezing effects of cryoprobes with arbitrary layouts (size, orientation, number).
• To improve computational efficiency and accuracy for cryoablation simulations.

Main Methods:

• A boundary heat source method was used to model heat transfer from cryoprobes.
• A fast parallel alternating direction explicit (PADE) finite difference method was employed for computation.
• A dynamic and conformal computational region was designed using shortest distance definition.

Main Results:

• The model accurately predicts temperature field evolution for multi-cryoprobe configurations.
• Significant computational acceleration was achieved with a 100-fold larger time step compared to explicit methods.
• Reduced computational region (at least 40% fewer voxels) and high parallel efficiency (8x speedup) were demonstrated.

Conclusions:

• The presented thermal model efficiently and accurately predicts cryoablation temperature fields.
• The model's computational advantages support its use in developing and improving clinical cryoablation procedures.
• This approach offers enhanced predictive capabilities for complex tissue structures and multi-cryoprobe setups.