Latency of subthalamic nucleus deep brain stimulation-evoked cortical activity as a potential biomarker for postoperative motor side effects
Introduction
Parkinson’s disease (PD) is a debilitating disorder that impacts approximately 1% of people over age 60 worldwide (de Lau and Breteler, 2006). Deep brain stimulation (DBS) improves the motor symptoms of PD; however, we lack fundamental knowledge about how it modulates brain activity and which neural circuits are critical for both the therapeutic and adverse effects of stimulation. Consequently, individual responses to DBS vary widely in efficacy and tolerability.
Although stimulation sites in dorsal subthalamic nucleus (STN) or in the zona incerta are often clinically effective (Butson et al., 2011, Herzog et al., 2004, Saint-Cyr et al., 2009), DBS contacts just millimeters apart can have dramatically different effects (Eisenstein et al., 2014, Martens et al., 2011, Steigerwald et al., 2016, Tommasi et al., 2008). This presumably results from variations in functional neuroanatomy surrounding the electrode, with multiple gray and white matter structures in close proximity. In particular, the STN and other established targets for movement disorders are directly adjacent to the internal capsule. Incidental capsular activation can worsen speech, gait, and bradykinesia, forcing some patients to trade bothersome side effects for efficacy or to undergo additional craniotomy for lead revision (Falowski and Bakay, 2016, Nestor et al., 2014, Tommasi et al., 2008, Xu et al., 2011).
To mitigate the unpredictable effects of stimulation, exhaustive behavioral testing has historically guided clinical decision-making during implantation and programming (Machado et al., 2006). Most centers still use electrophysiology to guide lead placement in awake patients, despite the discomforts of craniotomy, in order to verify efficacy and measure dose-limiting side effects at a given stimulation site. Recent advances in intraoperative imaging now allow targeting under general anesthesia and show some promise (Chen et al., 2017) but may produce more stimulation side effects versus awake procedures (Ho et al., 2018). Additionally, regardless of surgical targeting methods, postoperative DBS programming is a time-consuming, trial-and-error process (Krack et al., 2002), often taking weeks to months to achieve stable, effective settings (Volkmann et al., 2006). Because of its subjective and heuristic nature, this process can lead to unsatisfactory, sub-optimal outcomes, even with well-placed leads (Okun et al., 2005).
Predictive biomarkers to quickly identify DBS contacts for inclusion/exclusion could vastly simplify and expedite both DBS targeting (awake or asleep) and postoperative programming. Among a variety of candidate DBS biomarkers, local field potentials (LFPs) have been studied most extensively and show promise for guiding DBS therapy (Little and Brown, 2012). Notably, spectral power in the beta frequency range (10–30 Hz) in STN and cortex correlates with symptom severity and DBS efficacy, and can identify the STN dorsal border during surgery (Bronte-Stewart et al., 2009, de Hemptinne et al., 2015, Ince et al., 2010, Kühn et al., 2006, Swann et al., 2016, Tinkhauser et al., 2018). However, to our knowledge, little is known about whether LFPs predict stimulation side effects or the extent to which LFPs are altered under general anesthesia.
The neural responses evoked by DBS, time-locked to each stimulus pulse, are an alternative and potentially complementary biomarker. Early feasibility studies show that various components of STN, thalamic, and cortical evoked potentials (EPs) appear to correlate with efficacy (Baker et al., 2002, Gmel et al., 2015, Kent et al., 2015, Sinclair et al., 2019, Sinclair et al., 2018, Walker et al., 2012b, Walker et al., 2012a). Cortical EPs also result from capsular activation producing contralateral electromyography (EMG) activation (Ashby et al., 2001). Thus, beyond predicting efficacy, cortical EPs might additionally serve as a biomarker for motor side effects without the need for placing EMG electrodes on every potentially activated muscle.
We have previously shown that long latency cortical EPs can predict capsular motor side effects from DBS (Romeo et al., 2019). However, it is unknown whether this information can be obtained under general anesthesia. Here, we further investigate whether short latency cortical activation by STN DBS can predict the presence of motor side effects and explore whether short- and long-latency EPs could have utility under general anesthesia.
Section snippets
Participants
All patients were diagnosed with PD by a movement disorders specialist based on UK Brain Bank criteria, and DBS was recommended as part of routine care. We examined cortical EPs elicited by STN DBS in two cohorts (n = 19 total). To study the effects of general anesthesia on DBS evoked activity, we enrolled a cohort of patients who had been approved for DBS surgery (n = 11, 44 electrode contacts) and examined EPs both awake during lead placement and under general anesthesia during connection of
Demographics and clinical outcomes
The age and duration of disease on the day of surgery was 65.0 ± 6.2 and 7.4 ± 3.8 years, respectively (n = 19, mean ± SD). We implanted the left hemisphere in 12 of 19 cases (63%), and 7 of 19 of the participants were women (37%). Both the surgical and ambulatory cohorts showed significant improvement in the contralateral Unified Parkinson’s Disease Rating Scale (UPDRS) part 3 subscore “off” medications during intraoperative macrostimulation (mean change 8.4 ± 1.7, 42% improvement, p < 0.001,
Discussion
Here we provide early evidence that the precise timing of scalp potentials elicited by stimulation in the STN region can predict motor side effects from DBS. Very short latency EPs (<1 ms), most compatible with antidromic activation of the corticospinal/corticobulbar tracts, were associated with stimulation parameters that elicited capsular side effects. We observed this phenomenon at the STN target in two independent cohorts and across three different clinical venues (awake and under general
Funding
This work was supported by Medtronic, Inc.; the National Institute of Neurological Disorders and Stroke of the National Institutes of Health (grant no. UH3NS100553); and the Michael J. Fox Foundation. Funding sources had no involvement in the collection, analysis, or interpretation of data, or in the writing of this manuscript.
Author contributions
HW, BG, KS, and TM contributed to conception and design of the study. MA, CG, AN, BG, KS, TM, and HW contributed to data collection. ZT, MA, CG, AN, and HW contributed to data analysis. ZT, MA, CG, JB, and HW wrote the manuscript draft. All authors contributed to manuscript revisions, and have read and approved the submitted version.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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These authors contributed equally to this work.