Patient-specific prediction of 3D ablation zones via oncological feature-conditioned deep generative modeling: An in silico feasibility study

This study demonstrates the feasibility of deep generative modeling conditioned on MRI-derived oncological features for generating in silico 3D ablation zones. By leveraging biophysically validated simulation data, this model enables the virtual simulation and comparison of treatment outcomes from various electrode configurations and cancer morphologies, thereby refining the therapeutic strategy for each individual.