Fat fraction data-driven electrical properties digital twin model for guiding microwave ablation planning: a preliminary study

Motivation: In response to the lack of patient-specific electrical properties (EPs) in conventional ablation models, a fat fraction (FF) data-driven EPs digital twin model was proposed. Goal(s): To explore the effect of liver FF on EPs and develop an EPs digital twin model to guide ablation planning. Approach: The FF-EPs functions was created using liver-mimicking phantoms. The specific EPs data obtained via FF-EPs were assigned to the patient's digital twin model for ablation simulation. Results: Temperature field distributions can be obtained in ablation simulations by means of the EPs digital twin model. Impact: This approach offers a promising strategy for customizing ablative therapy, with the promise of more accurate patient-specific ablation predictions.