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Abstract #4841

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

Yinhao Ren1, Wenxia Ju1, Wenjun Yao2, Yaqing Jia1, Xiang Nan1, and Jijun Han1
1Anhui Medical University, Hefei, China, 2the Second Affiliated Hospita of Anhui Medical University, Hefei, China

Synopsis

Keywords: Thermometry/Thermotherapy, Electron Paramagnetic Resonance

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.

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