Semi-automated approaches to optimize deep brain stimulation parameters in Parkinson's disease.
Kenneth H Louie, Matthew N Petrucci, Logan L Grado and 6 others
PMID 34020662WHAT IT FOUND
In two Parkinson's patients with DBS, algorithm-guided frequency testing found the same setting that most reduced rigidity with fewer tests, but patients preferred lower frequencies than that setting.
This is proof-of-principle, not a therapy trial.
Key findings
01The algorithm estimated the same rigidity-minimizing frequencies as full testing: 155 Hz for participant 1 and 185 Hz for participant 2.
02The algorithm visit took 2.5 h, compared with 4 h for the full testing visit.
03Both participants preferred frequencies between 70 and 110 Hz, with strongest preference at 70 Hz for participant 1 and 89 Hz for participant 2, not the frequencies that most reduced rigidity.
STILL TO COME
How it was doneWhat they foundWhat it means for PTs
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What it does not show
Only two participants were tested, both with akinetic-rigid Parkinson's disease and disease durations of 9 and 16 years, so the findings may not apply to tremor-dominant or early Parkinson's disease. The study optimized only stimulation frequency and forearm rigidity. Amplitude, pulse width, and electrode contacts were fixed to clinical settings. Side effects were monitored by a clinician but were not quantified in the rigidity model, and total energy delivered was not controlled or compensated. The two visits were 4.5 and 9 months apart, so rigidity could have changed between tests. The algorithm did not clearly outperform simple equal-interval sampling in one participant, and equal-interval sampling had the smallest frequency range in the other participant. This is a proof-of-principle feasibility study, not a trial showing that the method improves patient outcomes.
Declared interests
Funding was reported from the Parkinson Study Group, Parkinson's Disease Foundation, MnDRIVE Brain Conditions Fellowship, National Institutes of Health, and CTSI.
The easy way to misread this
Do not conclude that algorithm-guided DBS programming improves patient care or that higher frequency is best. It tested two patients, optimized only forearm rigidity and frequency, and the patients preferred lower frequencies than the frequency that most reduced rigidity.