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Controlling Parkinson's Disease With Adaptive Deep Brain Stimulation

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Calculating deep brain stimulation amplitudes and power consumption by constrained optimization.

Ruben Cubo¹, Markus Fahlström^2,3, Elena Jiltsova⁴

¹Department of Information Technology, Uppsala University, Box 337, 75105 Uppsala, Sweden.

Journal of Neural Engineering

|December 8, 2018

Summary

Optimizing deep brain stimulation (DBS) settings using mathematical models can improve therapeutic outcomes and reduce power consumption. Patient-specific models ensure effective treatment while avoiding side effects and conserving battery life for neurological conditions.

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Area of Science:

Neurosurgery
Biomedical Engineering
Computational Neuroscience

Background:

Deep brain stimulation (DBS) is a crucial treatment for neurological and psychiatric disorders.
Individualized stimulation parameters are essential for DBS efficacy and safety.
Power consumption of the DBS pulse generator is a significant consideration due to battery limitations.

Purpose of the Study:

To compare target coverage and power consumption of clinical versus model-based patient-specific DBS settings.
To evaluate the effectiveness of constrained optimization in calculating optimal DBS parameters.
To assess the impact of optimized settings on therapeutic outcomes and battery life.

Main Methods:

Development of patient-specific brain models for five individuals undergoing DBS.
Utilizing mathematical optimization to determine stimuli amplitudes, considering constraints to avoid critical brain regions.
Estimating power consumption based on measured impedance and battery life for both clinical and optimized settings.

Main Results:

Clinical DBS settings were generally less aggressive than unconstrained model-based optimizations.
Optimized DBS settings that adhered to safety constraints closely resembled clinical values.
Model-based optimization highlighted the importance of specifying avoidance volumes for enhanced safety and efficacy.

Conclusions:

Mathematical models can streamline the process of determining optimal patient-specific DBS settings within safety and technological constraints.
Further research is needed to refine patient-specific anatomical safety constraints for DBS.
Optimizing DBS amplitude, considering power consumption, and specifying avoidance volumes are critical for improving treatment outcomes and battery longevity.