TuneS: Patient-specific model-based optimization of contact configuration in deep brain stimulation
Journal:
arXiv
Published Date:
Dec 19, 2024
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 demonstrate
that STN motor streamlines consistently receive a significant portion of the
allocated stimulation volume, suggesting that a consistent portion of the
stimulation should ideally focus on the STN motor streamlines. At the example
of a small cohort of Parkinson's disease patients, the value of model-based
contact predictions for assessing stimulation targets while observing
constraints is demonstrated. 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.
