Deep Brain Stimulation Electrode Placement Planning
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Solution Overview
Problem
Current deep brain stimulation technologies face challenges in simulating optimal coverage of multiple target regions and selecting the appropriate device for surgical implantation, particularly when dealing with non-spherical stimulation fields and multi-target approaches, which limits surgical flexibility and effectiveness.
Innovation Solution
A computer-implemented method for planning the position of an electric stimulation device that combines medical image data, target region information, and electrode geometry to determine optimal electrode placement, avoiding interference with avoidance regions, using iterative processes and search regions to ensure comprehensive coverage of target areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If spherical stimulation fields are used to allow virtual 360 degrees of possible approach vectors, then surgical flexibility is improved, but manufacturing precision and stimulation accuracy deteriorate because spherical fields do not account for directional capabilities of modern electrodes
Solution Approach 1:
The patent changes the mathematical model parameters from spherical symmetry to ellipsoidal/anisotropic fields that reflect actual electrode directional characteristics. This allows the simulation to accurately represent modern directional electrodes while maintaining multiple possible approach trajectories, thus resolving the contradiction between surgical flexibility and stimulation accuracy.
Solution Approach 2:
The system dynamically adjusts the stimulation field model based on the specific electrode type selected, transitioning between different field geometries (spherical for omnidirectional, ellipsoidal for directional). This dynamic adaptation allows the planning software to optimize for both surgical flexibility and stimulation precision depending on the chosen device configuration.
2Manufacturing precision
If directional stimulation systems with non-spherical fields are used, then stimulation accuracy is improved, but the number of valid approach vectors is limited, worsening surgical flexibility
Solution Approach 1:
The patent segments the surgical planning process into discrete electrode orientation options, where each segment represents a valid approach vector that satisfies both the directional stimulation requirements and surgical accessibility constraints. This segmentation allows systematic evaluation of multiple discrete options rather than treating the problem as continuous, thus maintaining surgical flexibility while ensuring stimulation accuracy.
Solution Approach 2:
The planning software serves multiple functions: it simulates directional stimulation fields, identifies valid approach vectors, ranks trajectories anatomically, and supports multi-target approaches. This multi-functionality allows the same system to address both the precision requirements of directional electrodes and the flexibility needs of surgical planning.
3Reliability
If simulation of multiple target regions is implemented, then therapeutic effectiveness is improved, but device complexity increases due to the need to coordinate stimulation across multiple targets
Solution Approach 1:
The patent merges multiple target region simulations into a unified planning framework that evaluates single-electrode configurations capable of stimulating multiple targets simultaneously. By combining the simulation of multiple targets into one integrated analysis, the system reduces the need for separate planning processes for each target, thus managing complexity while maintaining therapeutic effectiveness.
Data Source
AI summary
Disclosed is a computer-implemented medical data processing method for planning a position of an electric stimulation device for neurostimulation of at least two target regions (TV1, . . . , TVN) disposed in an anatomical body part of a patient's body, the electric stimulation device (7) comprising at least two electric contacts, the method comprising executing, on at least one processor of at least one computer (3), steps of: a) acquiring (S1.1), at the at least one processor, medical image data describing a digital image of the anatomical body part, wherein the anatomical body part contains at least two target regions (TV1, . . . , TVN); b) determining (S1.2), by the at least one processor and based on the medical image data, target position data describing a position of each target region (TV1, . . . , TVN) in the anatomical body part; c) acquiring (S1.3), at the at least one processor, electric stimulation device geometry data describing a distance between the at least two contacts of the electric stimulation device (7); d) determining (S1.4), by the at least one processor and based on the target position data, target distance data describing a distance between each pair of the at least two target regions; e) determining (S1.5), by the at least one processor and based on the target position data and the target distance data and the electric stimulation device geometry data, electric stimulation device position data describing a stimulation position which is a relative position between the at least two target regions (TV1, . . . , TVN) and the electric stimulation device (7) which allows for stimulation of the at least two target regions (TV1, . . . , TVN) by the electric stimulation device (7).