Deep brain stimulation atlas, AI may personalize Parkinson’s treatment

A research team from Mass General Brigham has developed a symptom atlas for Parkinson’s disease and an associated algorithm to inform personalized deep brain stimulation (DBS) treatments.

The researchers underscored that DBS has been demonstrated to improve four major Parkinson’s disease symptoms: tremor, bradykinesia, rigidity and axial symptoms. However, DBS does not improve all symptoms equally.

This knowledge led the research team to hypothesize that symptom improvement via DBS may hinge on which white matter tracts within the brain are stimulated during treatment.

To investigate this, the researchers explored which tracts were associated with improvements across the four symptom domains in 237 Parkinson’s patients treated with DBS. By homing in on the location of each patient’s DBS electrodes, the research team successfully mapped circuits associated with symptom improvement.

This analysis revealed that tremor symptoms improved with stimulation of tracts connected to the cerebellum and primary motor cortex, whereas bradykinesia improved following stimulation of the supplementary motor cortex. Rigidity symptoms were associated with the premotor cortex.

The research team further noted that axial symptoms have not been extensively studied in the context of DBS, but the analysis showed improvement in these symptoms after supplementary motor cortex and brainstem tract stimulation.

The researchers emphasized that these findings may be particularly valuable because axial symptoms – like gait and stability issues – often do not respond well to traditional DBS approaches or dopaminergic treatments.

The white tract maps revealed in the analysis were then incorporated into a symptom atlas designed to shed light on how different electrical stimulation sites impact Parkinson’s-related motor symptoms.

From there, the research team used the atlas to develop an algorithm to generate symptom-specific, personalized DBS treatment plans.

The tool, known as Cleartune, uses insights from the atlas to select optimal stimulation parameters in patients undergoing DBS. To test the algorithm, the researchers used the tool to inform DBS treatment for five Parkinson’s patients in Germany.

For four of these participants, the algorithm led to greater improvements in Parkinson’s symptoms than standard-of-care approaches. For the fifth patient, symptom improvement was comparable between Cleartune and the standard-of-care.

The research team hopes that the atlas and the algorithm will help advance DBS treatments for Parkinson’s.

“There is already strong evidence of improved quality of life for PD patients treated with DBS, but currently we still use a ‘one-size-fits-all’ approach to treatment,” said senior study author Andreas Horn, MD, PhD, a Mass General Brigham neurologist, in the press release. “The techniques we have developed will help us readily tailor DBS to what each patient specifically needs and improve DBS even further.”

Moving forward, the researchers will continue efforts to better map the brain’s circuitry, which could help refine personalized treatments for Parkinson’s and other conditions, like obsessive-compulsive disorder (OCD).

“This was an interdisciplinary effort to create the most precise atlas of symptom-specific pathways that we could,” stated first and corresponding author Nanditha Rajamani, PhD, of Mass General Brigham. “We went a long way to use anatomical information from many different sources and worked with highly skilled neuroanatomists to produce and validate this research. Going forward, this approach can be a framework for improving DBS treatments for other disorders as well.”