Computer-implemented Soft Tissue Emulation System and Method

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This invention provides a computer-implemented system and method that uses artificial neural networks (ANNs) to create digital twins of soft tissues (such as the heart or liver) from imaging data. These digital twins can accurately and quickly simulate how the tissue would respond over time to specific stimuli like heat or electrical pulses. This approach enables real-time modeling suitable for both preoperative planning and intraoperative decision-making, and can be implemented on portable devices.

Use CasesContent extracted from patent full text and abstract with AI.

• Personalized preoperative planning for cardiac surgery by simulating patient-specific heart tissue responses to electrical stimulation.
• Intraoperative guidance for surgeons to visualize tissue reactions in real time during procedures.
• Planning and optimization of liver tumor ablation (e.g., radio-frequency ablation) by simulating heat distribution and tissue response.
• Automatic determination of optimal electrode configuration and needle trajectories for liver cancer treatments based on patient imaging.
• Education and training tools for clinicians using patient-specific anatomical and physiological emulations.
• Development of portable (tablet/phone) applications for bedside or operating room use.

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• Enables real-time, patient-specific soft tissue simulation for clinical decision making and surgical planning.
• Improves accuracy of treatment planning by providing realistic, data-driven digital twins of organs.
• Reduces computational time and resource requirements compared to traditional biomechanical solvers, making real-time feedback feasible.
• Minimizes risks and improves outcomes by optimizing interventions (such as ablation) based on individualized tissue simulations.
• Supports both cloud-based and portable device (phone/tablet) deployment, increasing flexibility in clinical workflows.
• Parallelizable and scalable, suitable for processing large datasets and adapting to various soft tissue types and medical imaging.
• Reduces error propagation thanks to non-autoregressive modeling, increasing simulation reliability.

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Patent Abstract

A soft tissue emulation system, comprising: an input interface, configured to obtain imaging data of the soft tissue; a computing unit, configured to implement an artificial neural network, which is adapted to generate, using the obtained imaging data as input, and a biophysical model of the soft tissue, a digital twin of the soft tissue at different times, wherein the biophysical model describes the response of the soft tissue to thermal and/or electromechanical stimuli over time, and wherein the generation of the digital twin at one time is independent of the generation of the digital twin at another time; and an output interface, configured to output a representation of the soft tissue over time based on the digital twin generated by the artificial neural network.