Researchers at the University of California, San Francisco conducted a study on adaptive deep brain stimulation (aDBS) for Parkinson’s disease, a condition affecting over 10 million people worldwide. Deep brain stimulation (DBS) is a surgical treatment involving implanted electrodes connected to an internal pulse generator to improve movement symptoms. However, some patients may still experience fluctuating symptoms despite optimized stimulation. Adaptive DBS uses artificial intelligence to adjust stimulation intensity in real-time based on brain signals that track a patient’s symptoms, potentially reducing bothersome symptom fluctuations throughout the day.
The study involved four participants with Parkinson’s disease already using conventional DBS, who reported experiencing bothersome motor symptoms and fluctuations even with optimized stimulation. With adaptive DBS, participants saw a reduction in their most bothersome Parkinson’s disease-related symptoms by around 50% compared to conventional DBS, improving their quality of life. The researchers developed a data-driven analysis pipeline and embedded adaptive DBS algorithms in the research device to monitor and adjust stimulation intensity based on the patient’s condition, providing personalized treatment for each patient’s most bothersome symptoms.
Jean-Philippe Langevin, MD, a neurosurgeon not involved in the study, praised the research for its well-designed and robust approach, finding that adaptive stimulation during DBS was superior to chronic continuous stimulation for treating Parkinson’s symptoms. By delivering stimulation only when needed, adaptive DBS can reduce potential side effects and prolong the life of the implantable battery, potentially improving patient outcomes. While the technology for adaptive DBS is nearly ready for deployment, further studies with larger sample sizes could help validate and expand on the findings, ultimately benefiting patients with Parkinson’s disease.
Shabbar F. Danish, MD, chair of Neurosurgery at Jersey Shore University Medical Center, New Jersey, also commented on the study’s significance, emphasizing the need for continued refinement of treatments for Parkinson’s disease since there is currently no cure. Understanding brain signals that correlate with symptom clusters can lead to more targeted and effective treatments, improving the control of disease symptoms and enhancing the quality of life for patients. Adaptive DBS represents a promising advancement in the field, offering personalized treatment options and potentially reducing the disabling impact of Parkinson’s disease on individuals living with the condition.
Overall, the study on adaptive deep brain stimulation for Parkinson’s disease conducted by researchers at the University of California, San Francisco represents a significant advance in the field of neurology. By using artificial intelligence to adjust stimulation intensity based on real-time brain signals, adaptive DBS offers personalized treatment options that can reduce bothersome symptom fluctuations and improve the quality of life for patients with Parkinson’s disease. Further research with larger sample sizes and continued refinement of treatment strategies can help validate and expand on these findings, leading to better outcomes for individuals living with Parkinson’s disease.
