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Advances in Deep Brain Stimulation May Reduce Parkinson’s Disease Symptoms

CU Anschutz researchers probe new ways to improve treatment accuracy and expand access to innovations in therapy

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by Guest Contributor | December 16, 2024
Deep brain stimulation is shown with an electrode placed in a scan of a brain.

Research at the University of Colorado Anschutz Medical Campus could expand the reach and enhance the effectiveness of deep brain stimulation for Parkinson’s disease through advanced, computerized techniques, potentially benefiting some of the 90,000 people diagnosed each year in this country with the progressive movement disorder that has no cure.

Deep brain stimulation (DBS) surgically treats motor problems of Parkinson’s Disease (PD), such as tremors and involuntary movements that are no longer well-controlled by drugs alone. During DBS, surgeons implant electrodes in a targeted area of the brain, using MRI and sometimes recordings of brain cell activity to guide placement.

Symptoms of Parkinson’s disease commonly include trouble with movement and balance and tremor and muscle stiffness. Other symptoms can include depression, anxiety and problems with thinking and memory.

In a second procedure, surgeons place an implantable pulse generator (IPG), most typically under the collarbone. Like a heart pacemaker, the device sends electrical messages to specific areas of the brain that control movement. After surgery, patients are given a controller that turns the IGB on and off.

CU Anschutz scientists recently published a study on the new approaches to DBS in the journal NPJ Parkinson’s Disease.

Researchers include: John Thompson, PhD, associate professor in the departments of Neurosurgery and Neurology at the University of Colorado School of Medicine; Sunderland Baker, a Boettcher Scholar and Colorado College alum, now a PhD candidate in Biobehavioral Health at Penn State University; and Drew S. Kern, MD, MS, FAAN, co-director of the deep brain stimulation and advanced therapies in movement disorders programs and associate professor of the Movement Disorders Center in the departments of Neurology and Neurosurgery at the CU School of Medicine.

In the following Q&A, the three explain their findings and what they might mean for people with Parkinson’s disease.

The interview was edited for length and clarity.

Q&A Header

What role does brain neural activity play in Parkinson’s disease?

Our brains work by coordinated communication between groups of neurons. Neural activity can be measured in different frequency ranges and associated with distinct functions (e.g., EEG). In PD, the neural activity in a particular frequency range (13-30 Hz) known as beta measured in a region of the brain called the basal ganglia has been linked to severe motor problems. The higher power of these electrical signals, called the “beta peak,” is a hallmark of PD symptoms like rigidity and slowness of movement.

Because measuring beta peaks to program deep brain stimulation is a relatively new technology, clinicians are still learning how to use it. But it has shown promise in treating PD symptoms.

What is the biggest challenge for targeting beta peaks with deep brain stimulation?

The main challenge is figuring out the best way to identify the most therapeutically meaningful beta peak. It can be difficult. Although neurologists can use specific computer algorithms to help them target a certain frequency, the current process is very subjective and tedious. Our goal is to help relieve that burden and improve treatment.

What were the main findings from your NPJ Parkinson’s Disease study?

We evaluated and compared 10 different computer algorithms for peak identification from DBS electrodes in the brain. First, we identified differences in peak detection between expert clinicians and these algorithms. Next, we isolated different aspects of successful peak detection. Lastly, we assessed different electrode referencing strategies.

Our study added to research calling for a more general, objective strategy to detect beta peaks more easily. This work could help under-resourced clinics around the world as well as telemedicine by providing an efficient, computerized approach for streamlining DBS. More than 180,000 people worldwide could benefit from these improvements.

In future studies, we and other researchers will need to study algorithm performance in more patients and modify algorithms to improve their efficiency and utility.

What are next steps in improving DBS treatment of Parkinson’s disease?

What we learned in this paper could help dramatically improve the coming availability of a new technology called adaptive stimulation. This technology, developed for each patient’s unique symptoms and situation, will provide electrical stimulation that changes in near-real time based on the symptoms that patients are experiencing while they’re out and about during the day.

A recent small study in Nature Medicine highlighted how this personalized approach helped reduce symptoms in several patients. Adaptive stimulation will require doctors to make crucial decisions about which electrical signals to track. The algorithms we tested could help inform these decisions before patients are sent back home with the adaptive process.

Guest contributor: Carrie Printz is a Denver-based health sciences writer.

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John Thompson, PhD

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Drew S. Kern, MD, MS, FAAN