More than 10 million people globally live with Parkinson’s disease, and currently, there is no cure for this neurological condition that affects movement and balance. Deep brain stimulation (DBS) is a surgical treatment that can help alleviate symptoms of the disease, such as tremors and dyskinesia. However, some individuals may still experience movement issues even with DBS. Researchers from the University of California, San Francisco have found that adaptive deep brain stimulation (aDBS) that utilizes artificial intelligence (AI) can reduce the time a person experiences their most bothersome Parkinson’s disease-related symptom by around 50%.
In a study published in the journal Nature Medicine, researchers conducted a clinical trial with four participants with Parkinson’s disease who were already receiving conventional DBS treatment. The study found that aDBS using AI was able to alleviate participants’ most bothersome Parkinson’s disease-related symptoms by approximately 50% when compared to conventional DBS. This adaptive approach continuously monitors a patient’s brain signal to track symptoms and adjusts stimulation intensity in real-time, delivering the correct amount of stimulation needed to control symptoms effectively.
Jean-Philippe Langevin, MD, a board-certified neurosurgeon, praised the study’s design and results, noting that the findings are ground-breaking and offer potential benefits over continuous stimulation. Adaptive stimulation provides stimulation only when needed, potentially reducing side effects and prolonging the life of the implantable battery. By improving DBS therapy in this way, the quality of life for individuals with Parkinson’s disease could be positively impacted. While there is currently no cure for Parkinson’s disease, continuing to refine treatments like aDBS that target specific symptoms could be crucial for managing the condition in the future.
Shabbar F. Danish, MD, FAANS, chair of Neurosurgery at Jersey Shore University Medical Center, also emphasized the importance of advancing treatment options for Parkinson’s disease. He highlighted the need to understand the brain signals that correlate with different symptom clusters in order to create more targeted therapies. By expanding studies like the one from the University of California, San Francisco to a larger sample size, researchers and clinicians can gain further insights into the effectiveness of adaptive deep brain stimulation for Parkinson’s disease. This progress represents a substantial step forward for improving care and quality of life for individuals living with Parkinson’s disease.
The development of adaptive deep brain stimulation (aDBS) for Parkinson’s disease demonstrates significant progress in the field and could offer a promising treatment strategy for individuals with the condition. By utilizing artificial intelligence to continuously monitor brain signals and adjust stimulation intensity in real-time based on specific symptoms, aDBS has the potential to improve motor symptoms by reducing the time spent with bothersome symptoms. The study’s findings, which showed a 50% reduction in bothersome Parkinson’s disease-related symptoms compared to conventional DBS, highlight the impact of personalized, adaptive treatment approaches in enhancing quality of life for patients.
While current standard treatments like conventional DBS are effective in reducing movement problems associated with Parkinson’s disease, they may not be optimal for all patients. With the development and implementation of adaptive DBS algorithms that adjust stimulation based on individual needs and symptom changes, researchers and healthcare providers can tailor treatment plans to address specific challenges that individuals face. By individualizing adaptive DBS algorithms to target each patient’s most bothersome symptoms, researchers hope to continue making strides in improving outcomes and quality of life for those living with Parkinson’s disease.
