TuneS: Patient-specific model-based optimization of contact configuration in deep brain stimulation

TL;DR

TuneS shows promise as a research tool, enabling systematic assessment of DBS target effectiveness and facilitating constraint-aware optimization of stimulation parameters, and contributes to the broader understanding of effective DBS targeting strategies.

Abstract

Objective: The objective of this study is to develop and evaluate a systematic approach to optimize Deep Brain Stimulation (DBS) parameters, addressing the challenge of identifying patient-specific settings and optimal stimulation targets for various neurological and mental disorders. Methods: TuneS, a novel pipeline to predict clinically optimal DBS contact configurations based on predefined targets and constraints, is introduced. The method relies upon patient-specific models of stimulation spread and extends optimization beyond traditional neural structures to include automated, model-based targeting of streamlines. Results: Initial findings show that both the STN motor subdivision and STN motor streamlines are consistently engaged under clinical settings, while regions of avoidance receive minimal stimulation. Given these findings, the value of model-based contact predictions for assessing stimulation targets while observing anatomical constraints is demonstrated at the example of ten Parkinson's disease patients. The predicted settings were generally found to achieve higher target coverages while providing a better trade-off between maximizing target coverage and minimizing stimulation of regions associated with side effects. Conclusion: TuneS shows promise as a research tool, enabling systematic assessment of DBS target effectiveness and facilitating constraint-aware optimization of stimulation parameters. Significance: The presented pipeline offers a pathway to improve patient-specific DBS therapies and contributes to the broader understanding of effective DBS targeting strategies.

Figures (10)

• Figure 1: Schematic workflow of TuneS based on preoperative MRI and postoperative CT images BioRenderTuneSChart.
• Figure 2: Schematic illustration of the Boston Vercise Cartesia™ Directional Lead (left) and the Abbott's St. Jude Medical Infinity™ Directional Lead (right) with the contact labels used in this study. Note that the segmented contacts (A, B, C) are labeled in a clockwise direction.
• Figure 3: Graphical user interface of TuneS, enabling patient cohort processing, individual target and constraint selection, and model parameter modification.
• Figure 4: (a) DBS lead location relative to STN subdivisions (motor - green, associative - orange, limbic - yellow). (b) Reconstruction of the left lead in Patient 10 based on CT scans acquired three days post-surgery (lead at the border of the STN) and several months later (lead further from the STN). The apparent displacement of the lead relative to the STN subdivisions can be attributed to brain shift effects.
• Figure 5: Point-wise (left) and trajectory-wise (right) quantification of tract activation in a static model. Red points indicate locations where the electric field norm exceeds the activation threshold. In the trajectory-wise approach, entire trajectories are marked in red when at least one point along their course surpasses the threshold.