DBS Lead Trajectory Ranking Using Predicted Tissue Activation

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current methods for planning DBS lead trajectories lack the ability to predict the effectiveness of stimulation programs and tissue activation volumes, making it difficult to determine optimal lead positions that achieve therapeutic goals while avoiding critical structures.

Innovation Solution

A method and system that utilize preoperative imaging and reverse programming algorithms to predict tissue activation volumes and optimize stimulation parameters, ranking candidate lead positions based on overlap with target and avoidance structures, using cost functions and a priori rankings.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional DBS lead trajectory planning methods are used, then the implantation process is simpler, but the ability to predict tissue activation volumes and optimize stimulation parameters is insufficient

Engineering Contradiction:

Improveprediction accuracy of tissue activation volumeVSAvoidcomplexity of trajectory planning system

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs preliminary prediction of tissue activation volumes and optimization of stimulation parameters before the actual DBS lead implantation. By using preoperative imaging data and computational models to simulate different trajectory options and predict their effects, the system allows clinicians to select the optimal trajectory in advance, avoiding the need for trial-and-error adjustments after implantation.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates a virtual copy of the patient's brain anatomy using preoperative imaging data (MRI, CT scans) to build a computational model. This digital replica allows for simulation and prediction of tissue activation volumes for different lead trajectories without physically implanting the lead, enabling precise planning before the actual surgical procedure.

Inventive Principle:

Principle #26Copying

2Reliability

If multiple candidate lead positions are evaluated with optimized stimulation parameters, then the therapeutic efficacy is maximized, but the computational time and processing complexity increase

Engineering Contradiction:

Improvetherapeutic efficacy of DBSVSAvoidcomputational processing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system evaluates multiple candidate lead positions and stimulation parameters, but focuses computational resources on the most promising candidates identified through preliminary filtering. By assessing a subset of optimized parameters for each candidate position rather than exhaustively testing all possible combinations, the system achieves sufficient therapeutic optimization without excessive computational time.

Inventive Principle:

Principle #16Partial or excessive action

3Manufacturing precision

If the system predicts volume of tissue activated for each candidate position, then the precision of lead placement is improved, but the computational complexity and processing requirements increase

Engineering Contradiction:

Improveprecision of lead placementVSAvoidcomplexity of prediction algorithm

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system replaces complex mechanical trial-and-error lead placement procedures with computational prediction algorithms. Instead of physically implanting leads and adjusting positions based on empirical observation, the system uses preoperative imaging data and electromagnetic field models to predict tissue activation volumes computationally, enabling precise lead placement planning before surgery.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12567495B2Neuroanatomy-based search to optimize trajectory selection during DBS targeting

Publication Date: 2026.03.03 BOSTON SCI NEUROMODULATION CORP

AI summary

Methods and systems for planning a trajectory for implanting electrical stimulation leads in a patient's brain are described. The methods and systems rank candidate trajectories based on their expected therapeutic efficacies, as well as other criteria. Optimized stimulation parameters are determined for each of the candidate trajectories and therapeutic efficacies using the optimized parameters are predicted.