DBS Therapy Targeting via Non-Linear Fiber Tract Segmentation
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Solution Overview
Problem
Current deep brain stimulation (DBS) therapies lack the precision and effectiveness in targeting white matter fiber tracts, which respond non-linearly to electric field-induced activation, affecting distant neural structures.
Innovation Solution
A system and method for configuring DBS therapy that includes a receiver module for brain anatomy data, a voxel definition module to identify non-linear and linear response structures, and an optimizer to calculate therapy metrics using non-linear functions for non-linear voxels and linear functions for linear voxels, allowing for precise targeting of DBS therapy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DBS therapy uses traditional linear targeting methods, then the treatment covers a broad area of brain tissue, but it lacks precision in targeting white matter fiber tracts and activates distant neural structures unintentionally
Solution Approach 1:
The brain tissue is segmented into voxels with different response characteristics (linear and non-linear). White matter fiber tracts are identified and separated from gray matter structures, allowing differential stimulation strategies. The electrode array is segmented into multiple independently controllable electrodes, enabling selective activation of different tissue regions through fractional current distribution.
Solution Approach 2:
Different regions of brain tissue are assigned different response characteristics (linear vs. non-linear). The therapy configuration applies local quality by using non-linear functions to model fiber tract activation and linear functions for gray matter structures. This allows precise control over which structures are activated and to what degree, improving targeting precision while avoiding unintended activation.
2Adaptability or versatility
If DBS therapy activates white matter fiber tracts, then distant neural structures are affected, but this non-linear response makes it difficult to control and predict the extent of activation
Solution Approach 1:
The system incorporates feedback by using measured or estimated electric field distributions to update the non-linear activation models. The therapy configuration iteratively adjusts current amplitudes and electrode selections based on predicted activation patterns, comparing these against desired outcomes and refining the configuration to achieve reliable and predictable fiber tract activation.
Solution Approach 2:
The system changes parameters by varying current amplitude, pulse width, and electrode selection to achieve different activation patterns. Non-linear functions are used to model how small changes in current amplitude can lead to threshold-based activation of fiber tracts, allowing precise control over which structures are activated and to what degree, improving both versatility and predictability.
3Power
If DBS therapy uses high current amplitudes to ensure adequate stimulation, then more tissue is activated including non-target structures, but this increases the risk of activating avoid structures and causing side effects
Solution Approach 1:
The system uses partial action by distributing current across multiple electrodes in a fractional manner, with each electrode receiving a portion of the total current. This allows the cumulative effect to achieve adequate stimulation of target structures while keeping individual electrode current densities lower, reducing the risk of activating avoid structures and causing side effects.
Solution Approach 2:
The optimized therapy configuration acts as an intermediary between the electrode array and the brain tissue. By carefully selecting which electrodes to activate and at what current amplitudes, the system mediates the stimulation to preferentially activate desired target structures while avoiding harmful activation of adjacent avoid structures, thus reducing side effects.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enables accurate and precise targeting of DBS therapy by accounting for non-linear responses of white matter fiber tracts, potentially improving treatment outcomes for neurological disorders.
Implementation Method 1
white matter fiber tracts, respond in a non-linear manner to electric field-induced activation
Data Source
AI summary
Systems and methods for configuring neurostimulation systems to identify optimal therapies for use in a patient. Positional data for a lead implanted in the patient and anatomical data are obtained. Non-linear response structures are identified in the patient, and therapy metrics are generated using non-linear functions of the quantity of volume segments in the non-linear response structures that would be activated by a given therapy configuration including a combination of current fractionalization and current amplitude.