VOA Generation System Using Fiber-Specific Analysis
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Solution Overview
Problem
Current systems for determining the volume of activation (VOA) in anatomical stimulation, such as deep brain stimulation, are inefficient due to the complexity of inhomogeneous and anisotropic fibers, leading to inaccurate predictions and time-consuming trial-and-error methods for selecting optimal stimulation parameters.
Innovation Solution
A system and method that analyze shape parameters of neural elements, like fibers, to determine threshold stimulation settings for each fiber, using a look-up table populated with calculated threshold data, allowing for real-time estimation of VOA based on clinician-input parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional trial-and-error methods are used to select stimulation parameters, then clinicians can adjust parameters without complex computational models, but the process becomes time-consuming and expensive
Solution Approach 1:
The system pre-calculates and stores activation thresholds for multiple fiber types in lookup tables before clinical use. During the procedure, clinicians simply query these pre-computed tables with desired stimulation parameters to obtain immediate VOA predictions, eliminating the need for time-consuming real-time computations or trial-and-error adjustments
2Measurement precision
If detailed fiber-by-fiber analysis is performed to accurately predict VOA, then stimulation parameter accuracy is improved, but computational complexity and processing time increase
Solution Approach 1:
The system segments the continuous fiber population into discrete fiber types (e.g., pyramidal neurons, interneurons, axons) with characteristic properties. Each fiber type is analyzed separately with its own activation threshold calculations, allowing accurate VOA prediction while managing computational complexity through categorization
Solution Approach 2:
Fiber activation thresholds are pre-computed for each fiber type and stored in lookup tables before clinical use. The system categorizes fibers by type and pre-calculates their activation characteristics, so during the procedure only table lookups are needed rather than performing complex real-time computations
3Measurement precision
If real-time VOA calculation is performed for each stimulation parameter setting, then accurate predictions are provided, but processing time becomes impractically long
Solution Approach 1:
The system performs all computationally intensive fiber activation calculations beforehand and stores results in lookup tables organized by fiber type and stimulation parameters. During clinical use, the system quickly retrieves pre-computed thresholds from these tables based on the desired stimulation settings, providing immediate VOA predictions without real-time computation
Solution Approach 2:
The system creates simplified representations of complex fiber activation data in the form of lookup tables that contain pre-computed activation thresholds. These tables serve as efficient copies of the full computational model, allowing rapid queries during the procedure without requiring the original complex calculations
Data Source
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AI summary
A system and method for generating an estimated volume of activation (VOA) corresponding to settings applied to a stimulation leadwire includes a processor performing the following: determining, for each of a plurality of neural elements, one or more respective parameters characterizing an electrical distribution along the neural element, looking up the one or more parameters for each of the neural elements in a look-up table (LUT), obtaining threshold values for each of the neural elements recorded in the LUT in association with the looked-up parameters, comparing, for each of the neural elements, a value of the leadwire settings to each of the respective threshold value, estimating based on the comparisons which of the neural elements would be activated by the settings, and generating a structure corresponding to a region including the neural elements estimated to be activated.