Ablation Assistance Using Numeric Modeling for Cardiac Procedures
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Solution Overview
Problem
Current ablation procedures for cardiac arrhythmias lack precision and consistency, leading to uncertainties in effectively targeting and confirming the creation of lesions, which can result in incomplete or inappropriate tissue ablation, particularly when isolating pulmonary veins or creating transmural lesions across varying tissue thicknesses.
Innovation Solution
A system utilizing numerical modeling and processing circuitry to determine ablation parameters, including suggested energy delivery element positioning and energy levels, based on patient-specific anatomical and physiological information, to enhance the accuracy and confidence of lesion creation during ablation procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional ablation procedures are used, then the procedure can be performed with simple equipment, but the precision and consistency of lesion creation is insufficient
Solution Approach 1:
The system performs preliminary computational modeling and simulation before the actual ablation procedure to predict tissue ablation outcomes. The numerical model calculates expected lesion geometry, depth, and volume based on planned ablation parameters, allowing clinicians to optimize the ablation strategy in advance and achieve more precise lesion creation.
Solution Approach 2:
The system incorporates real-time feedback by comparing actual ablation outcomes with predicted outcomes from the numerical model. The model is updated based on measured tissue properties and ablation results, enabling continuous refinement of ablation parameters to maintain precision throughout the procedure.
2Reliability
If ablation is performed without numerical modeling, then the procedure is faster to initiate, but the confidence in successful lesion creation is reduced
Solution Approach 1:
The numerical model and computational predictions are prepared in advance before the ablation procedure begins. Pre-procedural planning using the model allows the clinical team to establish confidence in the ablation strategy beforehand, so that during the actual procedure, the focus can be on execution rather than calculation, minimizing time loss.
Solution Approach 2:
The system uses parameter changes in the numerical model to quickly adapt to different patient anatomies and tissue properties. By adjusting model parameters such as tissue conductivity, thermal properties, and electrode configuration, the system can generate reliable predictions for various scenarios without requiring complete re-modeling, thus maintaining reliability while reducing setup time.
3Measurement precision
If ablation targets are identified without computational guidance, then the procedure is simpler to perform, but the accuracy of targeting is insufficient
Solution Approach 1:
The numerical model acts as an intermediary between the clinician's ablation plan and the actual tissue ablation outcome. The model translates planned ablation parameters into predicted tissue effects, providing a computational layer that enhances target identification accuracy by showing the expected lesion geometry and confirming adequate coverage of arrhythmogenic tissue.
Solution Approach 2:
The system creates a virtual copy of the patient's anatomy and tissue properties in the numerical model. This digital twin allows for precise simulation and prediction of ablation outcomes without directly manipulating the actual tissue, enabling accurate target identification and optimization of ablation parameters before the real procedure.
4Manufacturing precision
If ablation energy is delivered without predictive modeling, then the energy delivery is simpler, but the consistency of transmural lesions is insufficient
Solution Approach 1:
The numerical model dynamically adjusts ablation predictions based on real-time changes in tissue properties, electrode position, and energy delivery parameters. This dynamic modeling capability allows the system to maintain consistent transmural lesion creation even when anatomical variations or procedural conditions change, by continuously updating the predicted lesion geometry and providing guidance for parameter adjustment.
Data Source
AI summary
An example system for use in ablating target tissue includes memory configured to store anatomical and/or physiological information of a patient and processing circuitry communicatively coupled to the memory. The processing circuitry is configured to, based on the anatomical information and/or the physiological information, determine ablation parameters, the ablation parameters including a suggested positioning of at least energy delivery element of at least one catheter and/or an amount of energy to be delivered via the at least one energy delivery element to the target tissue during ablation. The processing circuitry is configured to output, for display, a representation of at least one of a suggested positioning of the at least one energy delivery element during the ablation, a representation of the target tissue, or a representation of the predicted tissue volume that will be ablated after delivery of ablation energy.