Research Highlights Key Advancements in Implementing Adaptive Deep Brain Stimulation for Parkinson Disease

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Two studies conducted by UC San Francisco suggest that adaptive deep brain stimulation (aDBS) offers a transformative approach to treating Parkinson disease (PD) by providing round-the-clock, personalized care through an implanted device. According to the authors of the studies, this technology implements methods derived from AI to monitor a patient’s brain activity for changes in symptoms. Regular deep brain stimulation devices deliver constant electrical pulses to help manage symptoms, but these often fail to account for the natural fluctuations in symptoms that patients experience throughout the day, according to the investigators.¹

“This is the future of deep brain stimulation for Parkinson’s disease,” said senior study author Philip Starr, MD, PhD, the Dolores Cakebread Professor of Neurological Surgery, co-director, UCSF Movement Disorders and Neuromodulation Clinic, in a news release. “There’s been a great deal of interest in improving DBS therapy by making it adaptive and self-regulating, but it’s only been recently that the right tools and methods have been available to allow people to use this long-term in their homes.”

In the first study, researchers tested the aDBS system in four patients, comparing it with constant DBS. Results found that aDBS was able to reduce those symptoms by 50%, considered to be a significant improvement over standard therapy. Additionally, this system demonstrated efficacy in the use of the closed-loop system, a first for Parkinson's patients, as they carried out daily activities.

Additionally, the aDBS has shown promise for alleviating insomnia, which is common in Parkinson's patients but rarely addressed by current DBS systems. The second study, which was published in Nature Communications, demonstrating that the device could recognize brain patterns associated with sleep states and waking periods. Currently, a team led by Simon Little, MBBS, PhD, is conducting tests on algorithms aimed at improving sleep quality.¹

“The big shift we’ve made with adaptive DBS is that we’re able to detect, in real time, where a patient is on the symptom spectrum and match it with the exact amount of stimulation they need,” said Little, speaking to UC San Francisco.

According to the Parkinson’s Foundation, PD affects nearly one million people in the United States. By 2030, the number is expected to rise to 1.2 million people. Globally, around 10 million people are currently living with PD. While the incidence of the disease increases with age, 4% of patients are diagnosed before the age of 50 years. While both men and women can be diagnosed with PD, it is 1.5 times more likely for men to have the disease.

A 2022 study titled “Incidence of Parkinson’s Disease in North America” discovered that the incidence of Parkinson’s increases in the 65 and over age group. Further, the increase in incidence aligns with the growth of an aging population. The study also found that in the United States, PD is most common in the Rust Belt as well as Southern California, Southeastern Texas, Central Pennsylvania, and Florida.²

“This study is the most comprehensive assessment of PD incidence in North America based on five epidemiological (the study of a disease and its impact) sets of data to count the number of diagnoses in 2012. Prior PD incidence rates, based on smaller studies, were estimated to be in the 40,000–60,000 range per year. The new incidence rate is 1.5 times higher at nearly 90,000 cases annually,” reports the Parkinson’s Foundation.

References

1. Taming Parkinson’s disease with intelligent brain pacemakers. EurekAlert! August 19, 2024. Accessed August 21, 2024. https://www.eurekalert.org/news-releases/1054492

2. Statistics. Parkinson’s Foundation. Accessed August 21, 2024. https://www.parkinson.org/understanding-parkinsons/statistics