- More than 10 million people globally live with Parkinson’s disease, for which there is currently no cure.
- Deep brain stimulation (DBS) is a surgical treatment that helps alleviate some movement symptoms of the condition.
- People with Parkinson’s can still encounter movement issues when using current DBS.
- Researchers from the University of California, San Francisco found that adaptive deep brain stimulation that uses AI can reduce the time a person experiences their most bothersome Parkinson’s disease-related symptom by around 50%.
More than 10 million people around the world live with Parkinson’s disease — a neurological condition affecting a person’s movement and balance.
While there is currently no cure for Parkinson’s disease, there has been much research in the development of ways to alleviate the condition’s symptoms.
One of these is called deep brain stimulation (DBS) — a surgical procedure where electrodes are implanted into specific areas of a person’s brain that are connected to an internal pulse generator (IPG) placed under the skin near the collarbone, creating a “brain pacemaker.”
DBS helps to improve movement symptoms of Parkinson’s disease, such as tremor and dyskinesia.
“Although standard of care treatments like conventional DBS (cDBS) work well in reducing movement problems of Parkinson’s disease, some patients — even after optimization of stimulation intensity for cDBS — may still experience bothersome changes of symptoms throughout the day, for example in response to medications to treat Parkinson’s disease,” Stephanie Cernera, PhD, a postdoctoral fellow at The University of California, San Francisco (UCSF) explained to Medical News Today.
“As a result, on cDBS, patients may experience breakthrough symptoms, stemming from times of under- or overstimulation,” Cernera continued.
“Therefore, current therapies are not optimal for all patients. Understimulation would occur in times when a patient’s medication is wearing off and more stimulation is required than what is programmed for cDBS. Overstimulation may occur from times when the medication is active and stimulation-induced side effects would occur. These symptom fluctuations may negatively impact daily activities and quality of life,” she explained.
Alongside Carina R. Oehrn, MD, PhD and Lauren H. Hammer, MD, PhD, Cernera is co-first author of a new study looking at the use of adaptive deep brain stimulation (aDBS) for Parkinson’s disease.
In this small study, the researchers found that aDBS using artificial intelligence (AI) was able to alleviate participants’ most bothersome Parkinson’s disease-related symptoms by around 50% compared with conventional DBS.
The study was recently published in the journal Nature Medicine.
For this study, Cernera and her colleagues conducted a clinical trial with four participants with Parkinson’s disease already using conventional DBS.
“We knew that conventional DBS was not optimal in our four patients as they still had reported experiencing bothersome motor symptoms and motor fluctuations on clinically optimized conventional DBS,” Cernera explained. “We hypothesized that adaptive DBS would reduce their movement problems throughout the day, as it effectively increases and reduces stimulation when patients need it.”
“An adaptive DBS continuously monitors a brain signal that best tracks a patient’s symptoms,“ she continued. “Once the algorithm detects a change in the brain signal, it adjusts stimulation intensity in real-time. This means the device will deliver the correct amount of stimulation that the patient needs to adequately control their symptoms.”
To implement adaptive DBS, the authors developed a data-driven analysis pipeline that identifies brain signals that indicate changes in symptoms, as well as the adaptive DBS algorithms embedded within the research device.
“Current standard of care treatments for Parkinson’s disease — like conventional DBS — are not optimal for every patient,” Cernera said.
She added that:
“We decided to create this pipeline and algorithms as patients with Parkinson’s disease still experience bothersome symptom fluctuations. We wanted to create an algorithm that used the identified brain signal to automatically adjust stimulation amplitude in real-time to the patient’s specific needs. Unlike standard DBS, which provides a constant stimulation intensity, adaptive DBS would adjust the stimulation intensity based on the patient’s current condition as measured through the brain signal.”
During their study, the researchers found that adaptive DBS helped alleviate study participants’ most bothersome Parkinson’s disease-related symptoms by about 50% when compared to conventional DBS.
“In our study, we found that adaptive DBS reduced the time spent with bothersome motor symptoms by half compared to conventional DBS and improved patients’ quality of life,” Cernera said.
“To ensure adaptive DBS was not making the most bothersome motor symptom better at the expense of other motor or non-motor symptoms, we also monitored a variety of other motor (such as speech and gait impairments) and non-motor symptoms (sleep, mood, anxiety). We found that adaptive DBS was not different compared to conventional DBS, and in some cases, even improved other motor symptoms,” she added.
“We individualized each adaptive DBS algorithm to address each patient’s most bothersome symptom,” noted Cernera. “This led us to think that we’re changing something that really matters to the patient and will increase their quality of life. We were excited to confirm our hypotheses in our study.”
After reviewing this study, Jean-Philippe Langevin, MD, a board-certified neurosurgeon and director of Restorative Neurosurgery and Deep Brain Stimulation Program at Pacific Neuroscience Institute in Santa Monica, CA, who was not involved in this research, told MNT that it was very well-designed and robust, as it used a blinded and cross-over approach.
He also added that the findings are ground-breaking on multiple levels.
“The authors found that using adaptive stimulation during DBS was superior to chronic continuous stimulation to treat symptoms of Parkinson’s disease,” Langevin detailed.
“This is a critical finding because adaptive stimulation delivers on-demand stimulation as opposed to continuous constant stimulation. By delivering the stimulation only when needed, the DBS therapy can be improved by lowering the potential side-effects and also prolonging the life of the implantable battery. For these reasons, adaptive stimulation would be meaningful even if it was equal to continuous stimulation; but the authors have actually found that it was superior potentially because it provides added stimulation only when it is needed.”
– Jean-Philippe Langevin, MD
“Despite all available treatment and optimized therapy, Parkinson’s disease remains disabling for patients,” he continued.
“Any new or improved therapy efficacy would directly impact the quality of life of our patients. I believe that the most important step would be to expand the study to a larger sample size. The technology currently available on the market is already nearly able to deploy this treatment strategy,” noted Langevin.
MNT also spoke with Shabbar F. Danish, MD, FAANS, chair of Neurosurgery at Jersey Shore University Medical Center, New Jersey, about this study.
“This represents real progress in the field and a substantial step forward for the care of these patients,” Danish, who was not involved in the research, said.
“There is currently no cure for [Parkinson’s] disease. As a result, we must continue to refine our treatments so that the disease symptoms can be controlled. We need to understand in more depth which signals in the brain correlate with certain symptom clusters so that we can create more directed treatments,” he concluded.
