Liver tumor involvement by either primary or secondary cancers is responsible for over 1 million deaths per year worldwide. Image-guided percutaneous thermal ablation (PTA) has become a widely utilized option for patients not eligible for surgery, demonstrating similar 5-year overall survival rates between surgery and PTA. Achieving a 5 mm ablation margin has been shown to correlate with improved survival, however, achieving accurate needle placement and confirming sufficient ablation is challenging in the presence of liver deformation, needle artifacts, and inability to distinguish between the tumor boundary and ablation region post-PTA. This presentation will describe data demonstrating the need for accurate ablation measurement for improved outcomes, the emerging role of deep learning to provide segmentation of the liver, tumor, and ablation region, and the advances in precision of targeting the tumor and assessing the outcomes of the PTA through the use of biomechanical modeling of the liver.
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