Chronic embedded cortico-thalamic closed-loop deep brain stimulation for the treatment of essential tremor

Abstract

Deep brain stimulation (DBS) is an approved therapy for the treatment of medically refractory and severe movement disorders. However, most existing neurostimulators can only apply continuous stimulation [open-loop DBS (OL-DBS)], ignoring patient behavior and environmental factors, which consequently leads to an inefficient therapy, thus limiting the therapeutic window. Here, we established the feasibility of a self-adjusting therapeutic DBS [closed-loop DBS (CL-DBS)], fully embedded in a chronic investigational neurostimulator (Activa PC + S), for three patients affected by essential tremor (ET) enrolled in a longitudinal (6 months) within-subject crossover protocol (DBS OFF, OL-DBS, and CL-DBS). Most patients with ET experience involuntary limb tremor during goal-directed movements, but not during rest. Hence, the proposed CL-DBS paradigm explored the efficacy of modulating the stimulation amplitude based on patient-specific motor behavior, suppressing the pathological tremor on-demand based on a cortical electrode detecting upper limb motor activity. Here, we demonstrated how the proposed stimulation paradigm was able to achieve clinical efficacy and tremor suppression comparable with OL-DBS in a range of movements (cup reaching, proximal and distal posture, water pouring, and writing) while having a consistent reduction in energy delivery. The proposed paradigm is an important step toward a behaviorally modulated fully embedded DBS system, capable of delivering stimulation only when needed, and potentially mitigating pitfalls of OL-DBS, such as DBS-induced side effects and premature device replacement.

Fig. 1.. Patient-specific magnetic resonance imaging–computed tomography reconstruction and segmentation of cortical and thalamic regions in ET closed-loop patients.

(A) Subject ET01, (B) subject ET02, and (C) subject ET03 cortical segmentations. Red, postcentral gyrus; blue, precentral gyrus, known as primary motor cortex (M1). (D) Subcortical thalamic segmentation with overlaid DBS lead positioning based on surgical planning and all normalized to an MNI brain. The structures shown are ventralis oralis anterior (Voa; green), ventralis oralis posterior (Vop; magenta), ventralis intermediate nucleus (VIM; blue), and nucleus ventralis caudalis (VC; orange).

Fig. 2.. Training session for onboard movement detection.

(A) Setup for the training of the onboard weights used by the embedded LDA to actuate the stimulation. The patient is prompted to move (visual GO CUE) while data are being streamed through Nexus-D telemetry wand from the cortical strip (shown as a green strip in the patient head) to an external computer (the training algorithm output is not shown to the patient). (B) Task timeline of the recordings. The boxes with a dashed border indicate the un-cued actions that the subject took during the task. The patient was cued (GO CUE) to execute arm movement (with left or right arm) until the REST cue was delivered. The task was repeated interleaving the hands used in a randomized pattern. (C) Spectrogram collected from M1 through the telemetry wand, aligned with the executed cued movement (contralateral and ipsilateral). The spectrogram was used as features for a Fisher score feature selection algorithm, for which the output is shown in (D). One or two features were selected, and the Activa PC + S neurostimulator was set up accordingly. After identifying the features of interest, the same paradigm was repeated to obtain the weights and threshold for the stimulation delivery based on power features.

Fig. 3.. Task timeline and raw and spectral analyses with detection test bench.

(A) Task timeline of the recordings. Top: Cued-go hand opening and closing task. Bottom: Cued-go cup reaching task, where no rest cues were delivered. The boxes with a dashed border indicate the volitional actions the subject took during the task (following previous cued commands). (B) Data collected in a single patient (ET03) during a single cued-go cup reaching task along with contralateral and ipsilateral hand accelerations with respect to the side of implantation. The subjects were asked to prepare to move with the CUED hand (yellow). GO CUE (green) represents when the subjects were asked to reach the cup, and MOVEMENT (violet) represents when the patients proceeded to execute the movement. The bottom two plots show the outcome of the embedded movement detection (blue blocks indicate movement detection) and the stimulation estimate (considering the delivering during the contralateral/affected limb, it had an accuracy of 96.44%, a specificity of 95%, and a sensitivity of 97%). No DBS was delivered during this trial. Stimulation estimate is solely presented to show the feasibility of the paradigm (stimulation range = 0 to 2.5 V, ramp-up/down = 1.25 V/s). Therefore, tremor was present during each movement, unsuppressed. (C) Normalized event-related desynchronization and synchronization (ERD-ERS) spectrograms aligned to three events: cue, MO, and movement termination (MT) for contralateral and ipsilateral hand movements. (D) Zoomed section of raw recording from (B) during contralateral reaching movement.

Fig. 4.. Longitudinal clinical outcomes for CL-DBS during specific stimulation and movement events.

(A) Clinical TRS over 6-month visits across different DBS modalities. CL-DBS scores are presented starting with the month it was established in each patient. For patient ET01, the score for OL-DBS is missing on month 4 due to subject exhaustion. For patient ET02, month 3 scores were not assessed due to medical reasons unrelated to the study. (B) Tremor amplitude based on acceleration during the execution of the TRS clinical assessment shown in (A). For patient ET03, month 1 inertial data during TRS evaluation were not collected. (C) Diagram of the subdivisions of interest: SO, MO, time maximum stimulation amplitude reached (MSAR), MT, delay MO to SO (interval MO-SO), and delay MO to MSAR (interval MO-MSAR). (D) Tremor amplitude based on acceleration during the execution of the TRS clinical assessment over 6 monthly visits across different DBS modalities, as shown in (A) and (B). Top, tremor amplitude during the MO-SO interval; bottom, tremor amplitude during the MSAR-MT interval. For patient ET01, the score for OL-DBS is missing on month 4 due to subject exhaustion. For patient ET02, month 3 scores were not assessed due to medical reasons unrelated to the study. For patient ET03 month, inertial data during TRS evaluation were not collected. DBS OFF and OL-DBS settings do not have a ramp-up interval, and to achieve a comparison across different DBS settings (DBS OFF, OL-DBS, and CL-DBS), we use the MO-MSAR interval from the CL-DBS recorded during the same month. If no CL-DBS was executed during that month, we used the patient-matched MO-MSAR average.

Fig. 5.. Implementation of CL-DBS in patient affected by ET (ET01, third month).

Brain activity was recorded during a volitional reaching task with simulated drinking (patients reached for the cup, brought it close to their mouths, and put it back) along with ipsilateral and contralateral hand accelerometer traces. The violet boxes represent the movement initiation toward the target (cup). The second row shows the normalized spectrogram of the right M1 cortex collected chronically from a patient affected by ET and implanted with Activa PC + S. Two power bands centered at 15 and 25 Hz with 5-Hz bandwidth obtained with Fisher score feature selection were used as inputs to the linear discriminant analysis classifier embedded event detector (blue blocks indicate movement detection). The bottom row shows the output of the embedded event detector triggered closed-loop stimulation (stimulation range = 0 to 2 V, ramp-up/down = 2 V/s, frequency = 130 Hz, pulse width = 120 μs).

Fig. 6.. Performances of CL-DBS at monthly visits in all the enrolled subjects using the fully embedded onboard PC + S algorithm.

(A) Performances over the monthly clinical/research visit, such as accuracy and sensitivity of the CL-DBS classifier on top, and energy usage compared to energy usage (TEED) of continuous stimulation (with CL-DBS settings delivered as open-loop paradigm) at the bottom. (B) Average performances across months with CL-DBS during clinical/research visit. (C) Average performances of CL-DBS, including energy usage compared to energy usage (TEED) of continuous stimulation (with CL-DBS settings delivered as open-loop paradigm). (D) Characterization of the delays in the CL-DBS implementation (intervals MO-SO and MO-MSAR). (E) Energy saving with closed-loop stimulation compared to continuous stimulation (with CL-DBS settings delivered as open-loop paradigm) during clinical/research visit [as in (A) (bottom), (B), and (C)] and at short-term daily life usage. (F) TRS versus TEED scatter-plot, showing a subject-based decrease in the overall CL-DBS TEED compared to OL-DBS while maintaining a comparable TRS. TEEDs are normalized to the duration of the task to avoid bias due to each task length.