Sensing data and methodology from the Adaptive DBS Algorithm for Personalized Therapy in Parkinson's Disease (ADAPT-PD) clinical trial

Scott Stanslaski¹, Rebekah L S Summers², Lisa Tonder², Ye Tan², Michelle Case², Robert S Raike², Nathan Morelli², Todd M Herrington³, Martijn Beudel⁴, Jill L Ostrem⁵, Simon Little⁵, Leonardo Almeida⁶, Adolfo Ramirez-Zamora⁷, Alfonso Fasano^{8

9}, Travis Hassell¹⁰, Kyle T Mitchell¹¹, Elena Moro¹², Michal Gostkowski¹³, Nagaraja Sarangmat¹⁴, Helen Bronte-Stewart¹⁵; ADAPT-PD Investigators

Affiliations

¹ Medtronic Neuromodulation, Medtronic, Minneapolis, Minnesota, USA. scott.stanslaski@medtronic.com.
² Medtronic Neuromodulation, Medtronic, Minneapolis, Minnesota, USA.
³ Massachusetts General Hospital, Harvard Medical School, Boston, USA.
⁴ Department of Neurology, Amsterdam University Medical Centers, Amsterdam, Netherlands.
⁵ Department of Neurology, University of California San Francisco, San Francisco, USA.
⁶ Department of Neurology, University of Minnesota, Minneapolis, USA.
⁷ Department of Neurology, Shands at University of Florida, University of Florida, Gainesville, USA.
⁸ Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, University of Toronto, Toronto, ON, Canada.
⁹ Krembil Brain Institute, University of Toronto, Toronto, ON, Canada.
¹⁰ Department of Neurology, Vanderbilt University Medical Center, Nashville, USA.
¹¹ Duke University Movement Disorders Center, Duke University, Durham, USA.
¹² Grenoble Alpes University, Division of Neurology, Grenoble Institute of Neuroscience, CHU of Grenoble, Grenoble, France.
¹³ Center for Neurological Restoration, Cleveland Clinic Foundation, Cleveland, USA.
¹⁴ Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
¹⁵ Department of Neurology and Neurological Sciences, Stanford University, Stanford, USA.

PMID: 39289373
PMCID: PMC11408616
DOI: 10.1038/s41531-024-00772-5

Sensing data and methodology from the Adaptive DBS Algorithm for Personalized Therapy in Parkinson's Disease (ADAPT-PD) clinical trial

Scott Stanslaski et al. NPJ Parkinsons Dis. 2024.

. 2024 Sep 17;10(1):174.

doi: 10.1038/s41531-024-00772-5.

Authors

Affiliations

¹ Medtronic Neuromodulation, Medtronic, Minneapolis, Minnesota, USA. scott.stanslaski@medtronic.com.
² Medtronic Neuromodulation, Medtronic, Minneapolis, Minnesota, USA.
³ Massachusetts General Hospital, Harvard Medical School, Boston, USA.
⁴ Department of Neurology, Amsterdam University Medical Centers, Amsterdam, Netherlands.
⁵ Department of Neurology, University of California San Francisco, San Francisco, USA.
⁶ Department of Neurology, University of Minnesota, Minneapolis, USA.
⁷ Department of Neurology, Shands at University of Florida, University of Florida, Gainesville, USA.
⁸ Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, University of Toronto, Toronto, ON, Canada.
⁹ Krembil Brain Institute, University of Toronto, Toronto, ON, Canada.
¹⁰ Department of Neurology, Vanderbilt University Medical Center, Nashville, USA.
¹¹ Duke University Movement Disorders Center, Duke University, Durham, USA.
¹² Grenoble Alpes University, Division of Neurology, Grenoble Institute of Neuroscience, CHU of Grenoble, Grenoble, France.
¹³ Center for Neurological Restoration, Cleveland Clinic Foundation, Cleveland, USA.
¹⁴ Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
¹⁵ Department of Neurology and Neurological Sciences, Stanford University, Stanford, USA.

PMID: 39289373
PMCID: PMC11408616
DOI: 10.1038/s41531-024-00772-5

Abstract

Adaptive deep brain stimulation (aDBS) is an emerging advancement in DBS technology; however, local field potential (LFP) signal rate detection sufficient for aDBS algorithms and the methods to set-up aDBS have yet to be defined. Here we summarize sensing data and aDBS programming steps associated with the ongoing Adaptive DBS Algorithm for Personalized Therapy in Parkinson's Disease (ADAPT-PD) pivotal trial (NCT04547712). Sixty-eight patients were enrolled with either subthalamic nucleus or globus pallidus internus DBS leads connected to a Medtronic Percept^TM PC neurostimulator. During the enrollment and screening procedures, a LFP (8-30 Hz, ≥1.2 µVp) control signal was identified by clinicians in 84.8% of patients on medication (65% bilateral signal), and in 92% of patients off medication (78% bilateral signal). The ADAPT-PD trial sensing data indicate a high LFP signal presence in both on and off medication states of these patients, with bilateral signal in the majority, regardless of PD phenotype.

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Conflict of interest statement

This study is funded by Medtronic and employees of Medtronic have been involved in the conceptualization, design, data collection and analysis, and preparation of the manuscript as it is a pivotal trial of adaptive deep brain stimulation. S.S., R.S., L.T., Y.T., R.R., M.C., and N.M. are employees of Medtronic and may hold shares and/or stock options in the company. All investigators and their institutions received sponsorship for the conduct of the ADAPT-PD clinical trial from Medtronic. J.O. reports research support from Medtronic and Boston Scientific, and consulting payments from Abbott. L.A. has received honoraria from educational and advisory board consulting work for Medtronic and Boston Scientific. K.M. reports research support from Medtronic, Boston Scientific, and Surgical Information Sciences and consulting payments from Medtronic and Boston Scientific. T.H. reports research support from Medtronic and Boston Scientific and consulting payments from Medtronic. E.M. reports research support from Abbott and consulting payments from Abbott and Medtronic. E.M. is Associate Editor of npj Parkinson’s Disease. E.M. was not involved in the journal’s review of, or decisions related to, this manuscript. M.G. reports research support from Medtronic. A.R.Z. reports consulting for Medtronic. A.F. reports research support from Abbvie, Boston Scientific, Medtronic and consults for Abbvie, Abbott, Boston Scientific, Inbrain, Ipsen, Medtronic, Sunovion, Syneos Health and sits on advisory boards for Abbvie, Medtronic, Boston Scientific, Ceregate, Inbrain, Ipsen. A.F. also receives honoraria from Abbvie, Abbott, American Academy of Neurology, Boston Scientific, Brainlab, Ipsen, Medtronic, Merz, Movement Disorders Society, Sunovion, Paladin Labs, UCB. A.F. receives royalties from Springer. S.L. reports consulting for Iota Biosciences. N.S. has nothing to disclose. S.S. holds relevant patents to adaptive deep brain stimulation.

Figures

**Fig. 1. Clinician-identified local field potential (LFP) characteristics.**
a Peak LFP frequency on and off medication. b Peak LFP amplitude off medication. Signals combined between subthalamic nucleus and globus pallidus internus. Data included all hemispheres from subjects with unilateral or bilateral LFP signal meeting study eligibility criteria.

**Fig. 2. Automated algorithm-identified peaks in 71 nuclei and 45 patients on medication.**
a STN, (N = 53) and b GPi, (N = 18) peaks. The median and interquartile range power spectral density (PSD) are shown. PSDs are categorized by frequency: alpha (dark blue), low-beta (red) and high-beta (teal) bands plotted together.

**Fig. 3. Example of LFP signal visualization during aDBS delivery.**
BrainSense streaming feature enables visualization of stimulation amplitude adjustment during LFP signal fluctuation above or below LFP thresholds for single threshold (t = 20 s) (a) and dual threshold (t = 5 min) (b) mode aDBS; BrainSense Timeline feature demonstrating a 24-h interval of LFP signal fluctuation (yellow) and aDBS stimulation amplitude (pink) for single threshold (c) and dual threshold (d) mode aDBS. Note the LFP suppression during night hours. Chronic LFP chart illustrating time within threshold for single threshold (e) and dual threshold (f) mode aDBS. Last day of data in panels (e) and (f) only contain partial data from 53% and 46% of the day, respectively. Data extracted from a single participant in the ADAPT-PD trial.

**Fig. 4. ADAPT-PD trial visit schedule.**
The study schedule is formed by four general phases: the cDBS Baseline (orange), aDBS Setup and Adjustment (green), aDBS Evaluation (blue), and Long-term Follow-up (gold). Extended Access after Long-term Follow-Up was optional (gray). Participants exited the study due to signal artifact, inadequate LFP signal, or if no aDBS modes were found to be acceptable/tolerated.

**Fig. 5. Adaptive DBS as a Physiological Closed-Loop Control (PCLC) technology.**
Adapted from Technical Considerations for Medical Devices with Physiologic Closed-Loop Control Technology - Final Guidance for Industry and Food and Drug Administration Staff. In the ADAPT-PD trial, the Percept device PCLC operates with the LFP power thresholds serving as the system Set Points. The LFP thresholds are the inputs to the Comparator block, which continuously evaluates Feedback variable levels (i.e., LFP signal of interest power) in comparison to the LFP thresholds. The Error signal (LFP control signal above, between, or below threshold) triggers the Controller (aDBS algorithm) output signal to command the Actuator (Percept Simulation Engine) to adjust stimulation when appropriate.

**Fig. 6. Adaptive deep brain stimulation algorithmic modes.**
Single threshold mode (a) adapts stimulation amplitude up or down with a fast ramp (100’s of milliseconds) when the LFP control signal (i.e., LFP power) is above or below a pre-established threshold limit. Dual threshold mode (b) adapts stimulation with a slow ramp (min) when the LFP power of the control signal is above or below pre-established thresholds.

**Fig. 7. Example LFP peak detected by the Percept BrainSense Signal Test.**
Example power spectral density plot (PSD) shows 16.6 Hz LFP beta signal with 2.32 µVp that was used as the aDBS control signal for the Right STN of a study participant.

See this image and copyright information in PMC

References

1. Limousin, P. & Foltynie, T. Long-term outcomes of deep brain stimulation in Parkinson disease. Nat. Rev. Neurol.15, 234–242 (2019). - PubMed
1. Fasano, A., Aquino, C. C., Krauss, J. K., Honey, C. R. & Bloem, B. R. Axial disability and deep brain stimulation in patients with Parkinson disease. Nat. Rev. Neurol.11, 98–110 (2015). - PubMed
1. Fox, S. H. et al. International Parkinson and movement disorder society evidence-based medicine review: Update on treatments for the motor symptoms of Parkinson’s disease. Mov. Disord.33, 1248–1266 (2018). - PubMed
1. Schuepbach, W. M. M. et al. Neurostimulation for Parkinson’s disease with early motor complications. N. Engl. J. Med368, 610–622 (2013). - PubMed
1. Weaver, F. M. et al. Bilateral deep brain stimulation vs best medical therapy for patients with advanced Parkinson disease: a randomized controlled trial. JAMA301, 63–73 (2009). - PMC - PubMed

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Sensing data and methodology from the Adaptive DBS Algorithm for Personalized Therapy in Parkinson's Disease (ADAPT-PD) clinical trial

Affiliations

Sensing data and methodology from the Adaptive DBS Algorithm for Personalized Therapy in Parkinson's Disease (ADAPT-PD) clinical trial

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Grants and funding

LinkOut - more resources

Full Text Sources