Clinician Programmer for Deep Brain Stimulation Volume of Activation Prediction
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Solution Overview
Problem
Current deep brain stimulation (DBS) techniques rely on arbitrary trial-and-error for parameter selection, lacking visual aids and computational models to predict the volume of tissue influenced by stimulation, making it difficult and costly to achieve optimal therapy while minimizing side effects.
Innovation Solution
A system and method that determine a Stimulation Field Model (SFM) representing the volume of tissue likely to be stimulated by input DBS parameters, providing a graphical user interface to view and adjust these parameters, and calculating an optimal DBS parameter set to predict the Volume of Activation (VOA) for monopolar and bipolar electrode configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If trial-and-error parameter selection is used, then the simplicity of the process is maintained, but the time required and cost increase significantly while achieving optimal therapy
Solution Approach 1:
The system performs preliminary computational modeling to predict the volume of activation (VOA) before actual DBS parameter selection. By pre-calculating stimulation fields and their effects on anatomical structures, the system enables informed parameter choice without time-consuming trial-and-error during the procedure.
Solution Approach 2:
A computational intermediary model (the VOA prediction system) is introduced between the DBS parameters and the actual tissue response. This model includes electrical field simulations and anatomical structure mappings that mediate the relationship between input parameters and therapeutic outcomes, enabling prediction without direct physical experimentation.
2Ease of operation
If trial-and-error parameter selection is used, then the operational simplicity is maintained, but the cost increases significantly
Solution Approach 1:
The system performs preliminary computational modeling to predict the volume of activation (VOA) before actual DBS parameter selection. By pre-calculating stimulation fields and their effects on anatomical structures, the system enables informed parameter choice without time-consuming trial-and-error during the procedure.
Solution Approach 2:
A computational intermediary model (the VOA prediction system) is introduced between the DBS parameters and the actual tissue response. This model includes electrical field simulations and anatomical structure mappings that mediate the relationship between input parameters and therapeutic outcomes, enabling prediction without direct physical experimentation.
3Measurement precision
If computational models are introduced to predict VOA, then the accuracy of therapy prediction improves, but the device complexity increases
Solution Approach 1:
The system creates a computational copy or model of the patient's brain anatomy and electrical field properties. This virtual replica includes simplified representations of anatomical structures, tissue conductivity, and electrode configurations, allowing VOA prediction through simulation rather than direct measurement of the complex biological system.
Solution Approach 2:
The complex prediction problem is segmented into separate computational modules: anatomical structure identification, electrical field calculation, and VOA determination. Each module handles a specific aspect of the problem independently, making the overall complex system more manageable and easier to implement.
4Reliability
If visual aids and computational models are introduced, then the therapeutic effectiveness improves, but the ease of operation decreases
Solution Approach 1:
The system provides visual feedback to the clinician by displaying the predicted VOA overlaid on anatomical structures. This feedback mechanism shows the expected stimulation effects before treatment, allowing the clinician to adjust parameters based on real-time visualization rather than relying solely on trial-and-error, thus improving reliability while maintaining operational ease.
Data Source
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AI summary
A system and method for displaying a volume of activation (VOA) may include a processor that displays via a display device a model of a portion of a patient anatomy that includes anatomical structures, displays via the display device and overlying the display of the model a VOA associated by the processor with a set of anatomical stimulation parameter settings, the display of the VOA, and graphically identifies interactions between the displayed VOA and a first subset of the anatomical structures associated with one or more stimulation benefits and a second subset of the anatomical structures associated with one or more stimulation side effects, where the graphical identifications differ depending on whether the interaction is with the first subset or the second subset.