Adaptive DBS Algorithm for Personalized Therapy in Parkinson’s Disease: ADAPT-PD clinical trial methodology and early data (P1-11.002)

Brontë‐Stewart, Helen; Beudel, Martijn; Ostrem, Jill L.; Fasano, Alfonso; Almeida, Leonardo; Hassell, Travis J.; Moro, Elena; Gostkowski, Michal; Mitchell, Kyle T.; Hainque, Élodie; Sarangmat, Nagaraja; Stanslaski, Scott; Tonder, Lisa; Summers, Rebekah; Raike, Robert S.; Herrington, Todd M.

doi:10.1212/wnl.0000000000203099

Cited by 4 publications

(3 citation statements)

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“…This suggests individuals with PD could further benefit from aDBS. STN local field potential oscillations in a predefined beta band (13–30 Hz) are often proposed for adaptive (closed-loop) control in PD 2 , 17 , 18 based on the observation that resting subthalamic beta activity is elevated in the rigid/akinetic state and reduced when motor signs are alleviated by dopaminergic medication 19 or neurostimulation 20 . However, previous studies identified STN beta oscillations as control signals in the absence of stimulation.…”

Section: Introductionmentioning

confidence: 99%

Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in Parkinson’s disease

Oehrn

Cernera

Hammer

et al. 2023

Preprint

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1.AbstractDeep brain stimulation is a widely used therapy for Parkinson’s disease (PD) but currently lacks dynamic responsiveness to changing clinical and neural states. Feedback control has the potential to improve therapeutic effectiveness, but optimal control strategy and additional benefits of “adaptive” neurostimulation are unclear. We implemented adaptive subthalamic nucleus stimulation, controlled by subthalamic or cortical signals, in three PD patients (five hemispheres) during normal daily life. We identified neurophysiological biomarkers of residual motor fluctuations using data-driven analyses of field potentials over a wide frequency range and varying stimulation amplitudes. Narrowband gamma oscillations (65-70 Hz) at either site emerged as the best control signal for sensing during stimulation. A blinded, randomized trial demonstrated improved motor symptoms and quality of life compared to clinically optimized standard stimulation. Our approach highlights the promise of personalized adaptive neurostimulation based on data-driven selection of control signals and may be applied to other neurological disorders.

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Section: Introductionmentioning

confidence: 99%

Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in Parkinson’s disease

Oehrn

Cernera

Hammer

et al. 2023

Preprint

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“…Although the mechanisms of beta burst generation remain poorly understood, it is increasingly believed that bursts of longer duration and amplitude may be particularly detrimental to motor function in PD 11 . This finding has led to beta activity being used as a feedback signal in amplitude-responsive closed loop DBS, where stimulation is delivered only when beta amplitude rises above a certain threshold 12–16 . Studies reveal that beta triggered adaptive DBS (aDBS) is more effective than conventional continuous DBS 15,16 .…”

Section: Introductionmentioning

confidence: 99%

“…This finding has led to beta activity being used as a feedback signal in amplitude-responsive closed loop DBS, where stimulation is delivered only when beta amplitude rises above a certain threshold 12–16 . Studies reveal that beta triggered adaptive DBS (aDBS) is more effective than conventional continuous DBS 15,16 . Additionally, by virtue of selectively targeting a pathophysiological signal of interest, aDBS may offer additional benefits including reduced battery consumption and a lower incidence of stimulation induced side effects such as dyskinesias, gait impairment and speech impairment 17 .…”

Section: Introductionmentioning

confidence: 99%

Prediction of pathological subthalamic nucleus beta burst occurrence in Parkinson’s disease

Abdi-Sargezeh,

Shirani,

Sharma

et al. 2024

Preprint

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The cortico-basal ganglia network in Parkinson's disease (PD) is characterised by the emergence of transient episodes of exaggerated beta frequency oscillatory synchrony known as bursts. Although beta bursts of prolonged duration and amplitude are well recognised to have a detrimental effect on motor function in PD, the neurophysiological mechanisms leading to burst initiation remain poorly understood. Related to this is the question of whether there exist features of basal ganglia activity which can reliably predict the onset of beta bursts. Current state-of-the-art adaptive Deep Brain Stimulation (aDBS) algorithms for PD involve the reactive delivery of stimulation following burst detection and are unable to stimulate proactively so as to prevent burst onset. The discovery of a predictive biomarker would allow for such proactive stimulation, thereby offering further potential for improvements in both the efficacy and side effect profile of aDBS. Here we use deep neural networks to address the hypothesis that beta bursts can be predicted from invasive subthalamic nucleus (STN) recordings in PD patients. We developed a neural network which was able to predict bursts 31.6ms prior to their onset, with a high sensitivity and a low false positive rate (mean performance metrics: sensitivity = 84.8%, precision = 91.5%, area under precision recall curve = 0.87 and false positive rate = 7.6 per minute). Furthermore, by considering data segments that our network labelled as being predictive, we show that a dip in the beta amplitude (a fall followed by a subsequent rise) is a predictive biomarker for subsequent burst occurrence. Our findings demonstrate proof-of-principle for the feasibility of beta burst prediction and inform the development of a new type of intelligent DBS approach with the capability of stimulating proactively to prevent beta burst occurrence.

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Challenges and opportunities of acquiring cortical recordings for chronic adaptive deep brain stimulation

Herron,

Kullmann,

Denison

et al. 2024

Nat. Biomed. Eng

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Adaptive DBS Algorithm for Personalized Therapy in Parkinson’s Disease: ADAPT-PD clinical trial methodology and early data (P1-11.002)

Cited by 4 publications

References 0 publications

Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in Parkinson’s disease

Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in Parkinson’s disease

Prediction of pathological subthalamic nucleus beta burst occurrence in Parkinson’s disease

Challenges and opportunities of acquiring cortical recordings for chronic adaptive deep brain stimulation

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