The Role of Artificial Intelligence in Deep Brain Stimulation

Area of Science:

• Neurology
• Neurosurgery
• Biomedical Engineering

Background:

• Deep brain stimulation (DBS) effectively treats movement disorders like Parkinson's disease.
• Current DBS workflows are complex, leading to suboptimal outcomes due to lead misplacement and inefficient programming.
• There is a need for enhanced accuracy, reproducibility, and personalization in DBS therapy.

Purpose of the Study:

• To review the current and future applications of artificial intelligence (AI) in optimizing the DBS workflow.
• To explore how AI can improve surgical planning, lead placement, and postoperative programming.
• To enhance clinical efficiency and patient outcomes through AI-driven DBS.

Main Methods:

• This narrative review synthesizes existing literature on AI applications in DBS.
• The review examines AI's role across the entire DBS procedure, from planning to programming.
• Focus is placed on AI's potential to analyze complex data for pattern recognition and decision support.

Main Results:

• AI demonstrates significant potential in improving the accuracy of surgical planning and lead placement.
• AI tools can facilitate more precise and personalized postoperative programming of DBS devices.
• AI integration can lead to a more streamlined and efficient overall DBS workflow.

Conclusions:

• AI offers a transformative approach to overcoming the complexities of current deep brain stimulation procedures.
• Implementing AI in DBS can lead to enhanced precision, personalization, and improved patient outcomes for movement disorders.
• Future research should focus on validating and integrating AI tools into routine clinical practice for DBS therapy.