Patient, target, device, and program selection for DBS in Parkinson's disease: advancing toward precision care

Area of Science:

• Neurology
• Neurosurgery
• Biomedical Engineering

Background:

• Parkinson's disease (PD) management involves complex factors impacting deep brain stimulation (DBS) outcomes.
• Patient selection for DBS necessitates comprehensive interdisciplinary assessment of risks, benefits, and goals.

Purpose of the Study:

• To review patient selection criteria for DBS in Parkinson's disease.
• To summarize advancements in DBS hardware and programming strategies.
• To explore emerging technologies for personalized PD therapy.

Main Methods:

• Literature review integrating established and novel insights.
• Analysis of patient selection factors and target-specific benefits.
• Evaluation of technological progress in DBS hardware and programming.

Main Results:

• Patient-defined symptom priorities are crucial for selecting DBS targets.
• Technological innovations include sensing-based and image-guided programming.
• Emerging adaptive and automated programming tools enhance efficiency and personalization.

Conclusions:

• Optimizing DBS therapy for Parkinson's disease involves multidimensional patient selection.
• Hardware and programming advancements are driving progress towards personalized and efficient stimulation.
• Future strategies promise improved, tailored treatment for PD symptoms.