1
|
Sanger ZT, Henry TR, Park MC, Darrow D, McGovern RA, Netoff TI. Neural signal data collection and analysis of Percept™ PC BrainSense recordings for thalamic stimulation in epilepsy. J Neural Eng 2024; 21:012001. [PMID: 38211344 DOI: 10.1088/1741-2552/ad1dc3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 01/11/2024] [Indexed: 01/13/2024]
Abstract
Deep brain stimulation (DBS) using Medtronic's Percept™ PC implantable pulse generator is FDA-approved for treating Parkinson's disease (PD), essential tremor, dystonia, obsessive compulsive disorder, and epilepsy. Percept™ PC enables simultaneous recording of neural signals from the same lead used for stimulation. Many Percept™ PC sensing features were built with PD patients in mind, but these features are potentially useful to refine therapies for many different disease processes. When starting our ongoing epilepsy research study, we found it difficult to find detailed descriptions about these features and have compiled information from multiple sources to understand it as a tool, particularly for use in patients other than those with PD. Here we provide a tutorial for scientists and physicians interested in using Percept™ PC's features and provide examples of how neural time series data is often represented and saved. We address characteristics of the recorded signals and discuss Percept™ PC hardware and software capabilities in data pre-processing, signal filtering, and DBS lead performance. We explain the power spectrum of the data and how it is shaped by the filter response of Percept™ PC as well as the aliasing of the stimulation due to digitally sampling the data. We present Percept™ PC's ability to extract biomarkers that may be used to optimize stimulation therapy. We show how differences in lead type affects noise characteristics of the implanted leads from seven epilepsy patients enrolled in our clinical trial. Percept™ PC has sufficient signal-to-noise ratio, sampling capabilities, and stimulus artifact rejection for neural activity recording. Limitations in sampling rate, potential artifacts during stimulation, and shortening of battery life when monitoring neural activity at home were observed. Despite these limitations, Percept™ PC demonstrates potential as a useful tool for recording neural activity in order to optimize stimulation therapies to personalize treatment.
Collapse
Affiliation(s)
- Zachary T Sanger
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, United States of America
| | - Thomas R Henry
- Department of Neurology, University of Minnesota, Minneapolis, United States of America
| | - Michael C Park
- Department of Neurosurgery, University of Minnesota, Minneapolis, United States of America
- Department of Neurology, University of Minnesota, Minneapolis, United States of America
| | - David Darrow
- Department of Neurosurgery, University of Minnesota, Minneapolis, United States of America
| | - Robert A McGovern
- Department of Neurosurgery, University of Minnesota, Minneapolis, United States of America
| | - Theoden I Netoff
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, United States of America
| |
Collapse
|
2
|
Yang JC, Yang AI, Gross RE. Sensing-Enabled Deep Brain Stimulation in Epilepsy. Neurosurg Clin N Am 2024; 35:119-123. [PMID: 38000835 DOI: 10.1016/j.nec.2023.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2023]
Abstract
Deep brain stimulation has demonstrated efficacy in reducing seizure frequency in patients with drug-resistant epilepsy who may otherwise not be candidates for other surgical procedures. Recently, a clinical device that can monitor neural activity in the form of local field potentials around the deep brain stimulator lead implant site has been introduced. While this technology has been clinically adopted in other disorders treated with deep brain stimulation, such as Parkinson's disease, its application in epilepsy remains unclear. Previous research using investigational devices has suggested that specific frequency bands may correlate with clinical response to deep brain stimulation in epilepsy, but features of the clinical device may prevent its use. The authors present their experience with using this technology in epilepsy patients and describe some of its limitations. Ultimately, novel biomarkers will need to be identified to elucidate how neural activity at deep brain stimulation sites may change with clinical response.
Collapse
Affiliation(s)
- Jimmy C Yang
- Department of Neurological Surgery, The Ohio State University College of Medicine, Columbus, OH, USA; Department of Neurosurgery, Emory University, 1365 Clifton Road NE, Suite B6200, Atlanta, GA 30322, USA.
| | - Andrew I Yang
- Department of Neurosurgery, Emory University, 1365 Clifton Road NE, Suite B6200, Atlanta, GA 30322, USA
| | - Robert E Gross
- Department of Neurosurgery, Emory University, 1365 Clifton Road NE, Suite B6200, Atlanta, GA 30322, USA; Department of Neurology, Emory University School of Medicine, 1365 Clifton Road NE, Suite B6200, Atlanta, GA 30322
| |
Collapse
|
3
|
Baud MO, Proix T, Gregg NM, Brinkmann BH, Nurse ES, Cook MJ, Karoly PJ. Seizure forecasting: Bifurcations in the long and winding road. Epilepsia 2023; 64 Suppl 4:S78-S98. [PMID: 35604546 PMCID: PMC9681938 DOI: 10.1111/epi.17311] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 05/20/2022] [Accepted: 05/20/2022] [Indexed: 11/28/2022]
Abstract
To date, the unpredictability of seizures remains a source of suffering for people with epilepsy, motivating decades of research into methods to forecast seizures. Originally, only few scientists and neurologists ventured into this niche endeavor, which, given the difficulty of the task, soon turned into a long and winding road. Over the past decade, however, our narrow field has seen a major acceleration, with trials of chronic electroencephalographic devices and the subsequent discovery of cyclical patterns in the occurrence of seizures. Now, a burgeoning science of seizure timing is emerging, which in turn informs best forecasting strategies for upcoming clinical trials. Although the finish line might be in view, many challenges remain to make seizure forecasting a reality. This review covers the most recent scientific, technical, and medical developments, discusses methodology in detail, and sets a number of goals for future studies.
Collapse
Affiliation(s)
- Maxime O Baud
- Sleep-Wake-Epilepsy Center, Center for Experimental Neurology, NeuroTec, Department of Neurology, Inselspital Bern, University Hospital, University of Bern, Bern, Switzerland
- Wyss Center for Bio- and Neuro-Engineering, Geneva, Switzerland
| | - Timothée Proix
- Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Nicholas M Gregg
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Benjamin H Brinkmann
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Ewan S Nurse
- Graeme Clark Institute, University of Melbourne, Melbourne, Victoria, Australia
| | - Mark J Cook
- Graeme Clark Institute, University of Melbourne, Melbourne, Victoria, Australia
| | - Philippa J Karoly
- Graeme Clark Institute, University of Melbourne, Melbourne, Victoria, Australia
| |
Collapse
|
4
|
Schulze-Bonhage A, Bruno E, Brandt A, Shek A, Viana P, Heers M, Martinez-Lizana E, Altenmüller DM, Richardson MP, San Antonio-Arce V. Diagnostic yield and limitations of in-hospital documentation in patients with epilepsy. Epilepsia 2023; 64 Suppl 4:S4-S11. [PMID: 35583131 DOI: 10.1111/epi.17307] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 05/16/2022] [Accepted: 05/16/2022] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To determine the diagnostic yield of in-hospital video-electroencephalography (EEG) monitoring to document seizures in patients with epilepsy. METHODS Retrospective analysis of electronic seizure documentation at the University Hospital Freiburg (UKF) and at King's College London (KCL). Statistical assessment of the role of the duration of monitoring, and subanalyses on presurgical patient groups and patients undergoing reduction of antiseizure medication. RESULTS Of more than 4800 patients with epilepsy undergoing in-hospital recordings at the two institutions since 2005, seizures with documented for 43% (KCL) and 73% (UKF).. Duration of monitoring was highly significantly associated with seizure recordings (p < .0001), and presurgical patients as well as patients with drug reduction had a significantly higher diagnostic yield (p < .0001). Recordings with a duration of >5 days lead to additional new seizure documentation in only less than 10% of patients. SIGNIFICANCE There is a need for the development of new ambulatory monitoring strategies to document seizures for diagnostic and monitoring purposes for a relevant subgroup of patients with epilepsy in whom in-hospital monitoring fails to document seizures.
Collapse
Affiliation(s)
- Andreas Schulze-Bonhage
- Epilepsy Center, University Medical Center, University of Freiburg, Freiburg, Germany
- European Reference Network EpiCARE
| | - Elisa Bruno
- Division of Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Armin Brandt
- Epilepsy Center, University Medical Center, University of Freiburg, Freiburg, Germany
| | - Anthony Shek
- Division of Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Pedro Viana
- Division of Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Marcel Heers
- Epilepsy Center, University Medical Center, University of Freiburg, Freiburg, Germany
- European Reference Network EpiCARE
| | - Eva Martinez-Lizana
- Epilepsy Center, University Medical Center, University of Freiburg, Freiburg, Germany
- European Reference Network EpiCARE
| | | | - Mark Philip Richardson
- Division of Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Victoria San Antonio-Arce
- Epilepsy Center, University Medical Center, University of Freiburg, Freiburg, Germany
- European Reference Network EpiCARE
| |
Collapse
|
5
|
Yang AI, Raghu ALB, Isbaine F, Alwaki A, Gross RE. Sensing with deep brain stimulation device in epilepsy: Aperiodic changes in thalamic local field potential during seizures. Epilepsia 2023; 64:3025-3035. [PMID: 37607249 DOI: 10.1111/epi.17758] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 08/20/2023] [Accepted: 08/21/2023] [Indexed: 08/24/2023]
Abstract
OBJECTIVE Thalamic deep brain stimulation (DBS) is an effective therapeutic option in patients with drug-resistant epilepsy. Recent DBS devices with sensing capabilities enable chronic, outpatient local field potential (LFP) recordings. Whereas beta oscillations have been demonstrated to be a useful biomarker in movement disorders, the clinical utility of DBS sensing in epilepsy remains unclear. Our aim was to determine LFP features that distinguish ictal from inter-ictal states, which may aid in tracking seizure outcomes with DBS. METHODS Electrophysiology data were obtained from DBS devices implanted in the anterior nucleus (N = 12) or centromedian nucleus (N = 2) of the thalamus. Power spectra recorded during patient/caregiver-marked seizure events were analyzed with a method that quantitatively separates the oscillatory and non-oscillatory/aperiodic components of the LFP using non-parametric statistics, without the need for pre-specification of the frequency bands of interest. Features of the LFP parameterized using this algorithm were compared with those from inter-ictal power spectra recorded in clinic. RESULTS Oscillatory activity in multiple canonical frequency bands was identified from the power spectra in 86.48% of patient-marked seizure events. Delta oscillations were present in all patients, followed by theta (N = 10) and beta (N = 9). Although there were no differences in oscillatory LFP features between the ictal and inter-ictal states, there was a steeper decline in the 1/f slope of the aperiodic component of the LFP during seizures. SIGNIFICANCE Our work highlights the potential and shortcomings of chronic LFP recordings in thalamic DBS for epilepsy. Findings suggest that no single frequency band in isolation clearly differentiates seizures, and that features of aperiodic LFP activity may be clinically-relevant biomarkers of seizures.
Collapse
Affiliation(s)
- Andrew I Yang
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Ashley L B Raghu
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Faical Isbaine
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Abdulrahman Alwaki
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Robert E Gross
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, Georgia, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| |
Collapse
|
6
|
Chua MMJ, Vissani M, Liu DD, Schaper FLWVJ, Warren AEL, Caston R, Dworetzky BA, Bubrick EJ, Sarkis RA, Cosgrove GR, Rolston JD. Initial case series of a novel sensing deep brain stimulation device in drug-resistant epilepsy and consistent identification of alpha/beta oscillatory activity: A feasibility study. Epilepsia 2023; 64:2586-2603. [PMID: 37483140 DOI: 10.1111/epi.17722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 07/18/2023] [Accepted: 07/18/2023] [Indexed: 07/25/2023]
Abstract
OBJECTIVE Here, we report a retrospective, single-center experience with a novel deep brain stimulation (DBS) device capable of chronic local field potential (LFP) recording in drug-resistant epilepsy (DRE) and explore potential electrophysiological biomarkers that may aid DBS programming and outcome tracking. METHODS Five patients with DRE underwent thalamic DBS, targeting either the bilateral anterior (n = 3) or centromedian (n = 2) nuclei. Postoperative electrode lead localizations were visualized in Lead-DBS software. Local field potentials recorded over 12-18 months were tracked, and changes in power were associated with patient events, medication changes, and stimulation. We utilized a combination of lead localization, in-clinic broadband LFP recordings, real-time LFP response to stimulation, and chronic recordings to guide DBS programming. RESULTS Four patients (80%) experienced a >50% reduction in seizure frequency, whereas one patient had no significant reduction. Peaks in the alpha and/or beta frequency range were observed in the thalamic LFPs of each patient. Stimulation suppressed these LFP peaks in a dose-dependent manner. Chronic timeline data identified changes in LFP amplitude associated with stimulation, seizure occurrences, and medication changes. We also noticed a circadian pattern of LFP amplitudes in all patients. Button-presses during seizure events via a mobile application served as a digital seizure diary and were associated with elevations in LFP power. SIGNIFICANCE We describe an initial cohort of patients with DRE utilizing a novel sensing DBS device to characterize potential LFP biomarkers of epilepsy that may be associated with seizure control after DBS in DRE. We also present a new workflow utilizing the Percept device that may optimize DBS programming using real-time and chronic LFP recording.
Collapse
Affiliation(s)
- Melissa M J Chua
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Matteo Vissani
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - David D Liu
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Frederic L W V J Schaper
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Aaron E L Warren
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Rose Caston
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA
| | - Barbara A Dworetzky
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ellen J Bubrick
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Rani A Sarkis
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - John D Rolston
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA
| |
Collapse
|
7
|
Xu C, Qi L, Wang X, Schaper FLWVJ, Wu D, Yu T, Yan X, Jin G, Wang Q, Wang X, Huang X, Wang Y, Chen Y, Liu J, Wang Y, Horn A, Fisher RS, Ren L. Functional connectomic profile correlates with effective anterior thalamic stimulation for refractory epilepsy. Brain Stimul 2023; 16:1302-1309. [PMID: 37633491 DOI: 10.1016/j.brs.2023.08.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 08/19/2023] [Accepted: 08/21/2023] [Indexed: 08/28/2023] Open
Abstract
BACKGROUND Deep brain stimulation of the anterior nucleus of the thalamus (ANT-DBS) is an effective treatment for refractory epilepsy; however, seizure outcome varies among individuals. Identifying a reliable noninvasive biomarker to predict good responders would be helpful. OBJECTIVES To test whether the functional connectivity between the ANT-DBS sites and the seizure foci correlates with effective seizure control in refractory epilepsy. METHODS We performed a proof-of-concept pilot study of patients with focal refractory epilepsy receiving ANT-DBS. Using normative human connectome data derived from 1000 healthy participants, we investigated whether intrinsic functional connectivity between the seizure foci and the DBS site was associated with seizure outcome. We repeated this analysis controlling for the extent of seizure foci, distance between the seizure foci and DBS site, and using functional connectivity of the ANT instead of the DBS site to test the contribution of variance in DBS sites. RESULTS Eighteen patients with two or more seizure foci were included. Greater functional connectivity between the seizure foci and the DBS site correlated with more favorable outcome. The degree of functional connectivity accounted for significant variance in clinical outcomes (DBS site: |r| = 0.773, p < 0.001 vs ANT-atlas: |r| = 0.715, p = 0.001), which remained significant when controlling for the extent of the seizure foci (|r| = 0.773, p < 0.001) and the distance between the seizure foci and DBS site (|r| = 0.777, p < 0.001). Significant correlations were independent of variance in the DBS sites (|r| = 0.148, p = 0.57). CONCLUSION These findings suggest that functional connectomic profile is a potential reliable non-invasive biomarker to predict ANT-DBS outcomes. Accordingly, the identification of ANT responders could decrease the surgical risk for patients who may not benefit and optimize the cost-effective allocation of health care resources.
Collapse
Affiliation(s)
- Cuiping Xu
- National Center for Neurological Disorders, Beijing, China; Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Lei Qi
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Xueyuan Wang
- National Center for Neurological Disorders, Beijing, China; Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Frédéric L W V J Schaper
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, United States
| | - Di Wu
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Tao Yu
- National Center for Neurological Disorders, Beijing, China; Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Xiaoming Yan
- National Center for Neurological Disorders, Beijing, China; Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Guangyuan Jin
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Qiao Wang
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Xiaopeng Wang
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Xinqi Huang
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Yuke Wang
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Yuanhong Chen
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Jinghui Liu
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Yuping Wang
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China
| | - Andreas Horn
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, United States; Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany; MGH Neurosurgery & Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology, Massachusetts General Hospital, Harvard Medical School, United States
| | - Robert S Fisher
- Department of Neurology and Neurological Sciences and Neurosurgery by Courtesy, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Liankun Ren
- National Center for Neurological Disorders, Beijing, China; Department of Neurology, Xuanwu Hospital, Clinical Center for Epilepsy, Capital Medical University, Beijing, China; Chinese Institute for Brain Research, Beijing, China.
| |
Collapse
|
8
|
Fleming JE, Benjaber M, Toth R, Zamora M, Landin K, Kavoosi A, Ottoway J, Gillbe T, Piper RJ, Noone T, Campbell H, Gillbe I, Kaliakatsos M, Tisdall M, Valentín A, Denison T. An embedded intracranial seizure monitor for objective outcome measurements and rhythm identification. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-6. [PMID: 38083730 PMCID: PMC7615373 DOI: 10.1109/embc40787.2023.10340850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Providing clinicians with objective outcomes of neuromodulation therapy is a key unmet need, especially in emerging areas such as epilepsy and mood disorders. These diseases have episodic behavior and circadian/multidien rhythm characteristics that are difficult to capture in short clinical follow-ups. This work presents preliminary validation evidence for an implantable neuromodulation system with integrated physiological event monitoring, with an initial focus on seizure tracking for epilepsy. The system was developed to address currently unmet requirements for patients undergoing neuromodulation therapy for neurological disorders, specifically the ability to sense physiological data during stimulation and track events with seconds-level granularity. The system incorporates an interactive software tool to enable optimal configuration of the signal processing chain on an embedded implantable device (the Picostim-DyNeuMo Mk-2) including data ingestion from the device loop recorder, event labeling, generation of filter and classification parameters, as well as summary statistics. When the monitor parameters are optimized, the user can wirelessly update the system for chronic event tracking. The simulated performance of the device was assessed using an in silico model with human data to predict the real-time device performance at tracking recorded seizure activity. The in silico performance was then compared against its performance in an in vitro model to capture the full environmental constraints such as sensing during stimulation at the tissue electrode interface. In vitro modeling demonstrated comparable results to the in silico model, providing verification of the software tool and model. This study provides validation evidence of the suitability of the proposed system for tracking longitudinal seizure activity. Given its flexibility, the event monitor can be adapted to track other disorders with episodic and rhythmic symptoms represented by bioelectrical behavior.Clinical relevance-An implantable neuromodulation system is presented that enables chronic tracking of physiological events in disease. This physiological monitor provides the basis for longitudinal assessments of therapy outcomes for patients, such as those with epilepsy where objective identification of patient seizure activity and rhythms might help guide therapy optimization. The system is configurable for other disease states such as Parkinson's disease and mood disorders.
Collapse
Affiliation(s)
- John E. Fleming
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
- Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford, Oxford OX3 7DQ, UK
| | - Moaad Benjaber
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
- Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford, Oxford OX3 7DQ, UK
| | - Robert Toth
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
- Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford, Oxford OX3 7DQ, UK
| | - Mayela Zamora
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
- Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford, Oxford OX3 7DQ, UK
| | - Kei Landin
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
- Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford, Oxford OX3 7DQ, UK
| | - Ali Kavoosi
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
- Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford, Oxford OX3 7DQ, UK
| | | | | | - Rory J. Piper
- Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Department of Neurosurgery, Great Ormond Street Hospital, London WC1N 3JH, UK
| | | | | | | | - Marios Kaliakatsos
- Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
| | - Martin Tisdall
- Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
- Department of Neurosurgery, Great Ormond Street Hospital, London WC1N 3JH, UK
| | - Antonio Valentín
- Department of Basic and Clinical Neuroscience, King’s College London, London SE5 9RT, UK
| | - Timothy Denison
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
- Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford, Oxford OX3 7DQ, UK
| |
Collapse
|
9
|
Miller KJ, Müller KR, Valencia GO, Huang H, Gregg NM, Worrell GA, Hermes D. Canonical Response Parameterization: Quantifying the structure of responses to single-pulse intracranial electrical brain stimulation. PLoS Comput Biol 2023; 19:e1011105. [PMID: 37228169 DOI: 10.1371/journal.pcbi.1011105] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 04/14/2023] [Indexed: 05/27/2023] Open
Abstract
Single-pulse electrical stimulation in the nervous system, often called cortico-cortical evoked potential (CCEP) measurement, is an important technique to understand how brain regions interact with one another. Voltages are measured from implanted electrodes in one brain area while stimulating another with brief current impulses separated by several seconds. Historically, researchers have tried to understand the significance of evoked voltage polyphasic deflections by visual inspection, but no general-purpose tool has emerged to understand their shapes or describe them mathematically. We describe and illustrate a new technique to parameterize brain stimulation data, where voltage response traces are projected into one another using a semi-normalized dot product. The length of timepoints from stimulation included in the dot product is varied to obtain a temporal profile of structural significance, and the peak of the profile uniquely identifies the duration of the response. Using linear kernel PCA, a canonical response shape is obtained over this duration, and then single-trial traces are parameterized as a projection of this canonical shape with a residual term. Such parameterization allows for dissimilar trace shapes from different brain areas to be directly compared by quantifying cross-projection magnitudes, response duration, canonical shape projection amplitudes, signal-to-noise ratios, explained variance, and statistical significance. Artifactual trials are automatically identified by outliers in sub-distributions of cross-projection magnitude, and rejected. This technique, which we call "Canonical Response Parameterization" (CRP) dramatically simplifies the study of CCEP shapes, and may also be applied in a wide range of other settings involving event-triggered data.
Collapse
Affiliation(s)
- Kai J Miller
- Dept of Neurological Surgery, Mayo Clinic, Rochester, Minnesota, United States of America
- Dept of Biomedical Engineering & Physiology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Klaus-Robert Müller
- Google Research, Brain Team, Berlin, Germany
- Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Berlin, Germany
- Dept of Artificial Intelligence, Korea University, Seoul, Republic of Korea
- Max Planck Institute for Informatics, Saarbrücken, Germany
| | - Gabriela Ojeda Valencia
- Dept of Biomedical Engineering & Physiology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Harvey Huang
- Medical Scientist Training Program, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Nicholas M Gregg
- Dept of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Gregory A Worrell
- Dept of Biomedical Engineering & Physiology, Mayo Clinic, Rochester, Minnesota, United States of America
- Dept of Neurology, Mayo Clinic, Rochester, Minnesota, United States of America
| | - Dora Hermes
- Dept of Biomedical Engineering & Physiology, Mayo Clinic, Rochester, Minnesota, United States of America
| |
Collapse
|
10
|
Satzer D, Wu S, Henry J, Doll E, Issa NP, Warnke PC. Ambulatory Local Field Potential Recordings from the Thalamus in Epilepsy: A Feasibility Study. Stereotact Funct Neurosurg 2023; 101:195-206. [PMID: 37232010 DOI: 10.1159/000529961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 02/24/2023] [Indexed: 05/27/2023]
Abstract
INTRODUCTION Stimulation of the thalamus is gaining favor in the treatment of medically refractory multifocal and generalized epilepsy. Implanted brain stimulators capable of recording ambulatory local field potentials (LFPs) have recently been introduced, but there is little information to guide their use in thalamic stimulation for epilepsy. This study sought to assess the feasibility of chronically recording ambulatory interictal LFP from the thalamus in patients with epilepsy. METHODS In this pilot study, ambulatory LFP was recorded from patients who underwent sensing-enabled deep brain stimulation (DBS, 2 participants) or responsive neurostimulation (RNS, 3 participants) targeting the anterior nucleus of the thalamus (ANT, 2 electrodes), centromedian nucleus (CM, 7 electrodes), or medial pulvinar (PuM, 1 electrode) for multifocal or generalized epilepsy. Time-domain and frequency-domain LFP was investigated for epileptiform discharges, spectral peaks, circadian variation, and peri-ictal patterns. RESULTS Thalamic interictal discharges were visible on ambulatory recordings from both DBS and RNS. At-home interictal frequency-domain data could be extracted from both devices. Spectral peaks were noted at 10-15 Hz in CM, 6-11 Hz in ANT, and 19-24 Hz in PuM but varied in prominence and were not visible in all electrodes. In CM, 10-15 Hz power exhibited circadian variation and was attenuated by eye opening. CONCLUSION Chronic ambulatory recording of thalamic LFP is feasible. Common spectral peaks can be observed but vary between electrodes and across neural states. DBS and RNS devices provide a wealth of complementary data that have the potential to better inform thalamic stimulation for epilepsy.
Collapse
Affiliation(s)
- David Satzer
- Department of Neurological Surgery, University of Chicago, Chicago, Illinois, USA
| | - Shasha Wu
- Department of Neurology, University of Chicago, Chicago, Illinois, USA
| | - Julia Henry
- Department of Pediatrics, Child Neurology Section, University of Chicago, Chicago, Illinois, USA
| | - Emily Doll
- Department of Pediatrics, Child Neurology Section, University of Chicago, Chicago, Illinois, USA
| | - Naoum P Issa
- Department of Neurology, University of Chicago, Chicago, Illinois, USA
| | - Peter C Warnke
- Department of Neurological Surgery, University of Chicago, Chicago, Illinois, USA
| |
Collapse
|
11
|
Piper RJ, Richardson RM, Worrell G, Carmichael DW, Baldeweg T, Litt B, Denison T, Tisdall MM. Towards network-guided neuromodulation for epilepsy. Brain 2022; 145:3347-3362. [PMID: 35771657 PMCID: PMC9586548 DOI: 10.1093/brain/awac234] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 05/30/2022] [Accepted: 06/16/2022] [Indexed: 11/30/2022] Open
Abstract
Epilepsy is well-recognized as a disorder of brain networks. There is a growing body of research to identify critical nodes within dynamic epileptic networks with the aim to target therapies that halt the onset and propagation of seizures. In parallel, intracranial neuromodulation, including deep brain stimulation and responsive neurostimulation, are well-established and expanding as therapies to reduce seizures in adults with focal-onset epilepsy; and there is emerging evidence for their efficacy in children and generalized-onset seizure disorders. The convergence of these advancing fields is driving an era of 'network-guided neuromodulation' for epilepsy. In this review, we distil the current literature on network mechanisms underlying neurostimulation for epilepsy. We discuss the modulation of key 'propagation points' in the epileptogenic network, focusing primarily on thalamic nuclei targeted in current clinical practice. These include (i) the anterior nucleus of thalamus, now a clinically approved and targeted site for open loop stimulation, and increasingly targeted for responsive neurostimulation; and (ii) the centromedian nucleus of the thalamus, a target for both deep brain stimulation and responsive neurostimulation in generalized-onset epilepsies. We discuss briefly the networks associated with other emerging neuromodulation targets, such as the pulvinar of the thalamus, piriform cortex, septal area, subthalamic nucleus, cerebellum and others. We report synergistic findings garnered from multiple modalities of investigation that have revealed structural and functional networks associated with these propagation points - including scalp and invasive EEG, and diffusion and functional MRI. We also report on intracranial recordings from implanted devices which provide us data on the dynamic networks we are aiming to modulate. Finally, we review the continuing evolution of network-guided neuromodulation for epilepsy to accelerate progress towards two translational goals: (i) to use pre-surgical network analyses to determine patient candidacy for neurostimulation for epilepsy by providing network biomarkers that predict efficacy; and (ii) to deliver precise, personalized and effective antiepileptic stimulation to prevent and arrest seizure propagation through mapping and modulation of each patients' individual epileptogenic networks.
Collapse
Affiliation(s)
- Rory J Piper
- Department of Neurosurgery, Great Ormond Street Hospital, London, UK
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, USA
| | | | | | - Torsten Baldeweg
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Brian Litt
- Department of Neurology and Bioengineering, University of Pennsylvania, Philadelphia, USA
| | | | - Martin M Tisdall
- Department of Neurosurgery, Great Ormond Street Hospital, London, UK
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| |
Collapse
|
12
|
Löscher W, Worrell GA. Novel subscalp and intracranial devices to wirelessly record and analyze continuous EEG in unsedated, behaving dogs in their natural environments: A new paradigm in canine epilepsy research. Front Vet Sci 2022; 9:1014269. [PMID: 36337210 PMCID: PMC9631025 DOI: 10.3389/fvets.2022.1014269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 09/26/2022] [Indexed: 11/25/2022] Open
Abstract
Epilepsy is characterized by unprovoked, recurrent seizures and is a common neurologic disorder in dogs and humans. Roughly 1/3 of canines and humans with epilepsy prove to be drug-resistant and continue to have sporadic seizures despite taking daily anti-seizure medications. The optimization of pharmacologic therapy is often limited by inaccurate seizure diaries and medication side effects. Electroencephalography (EEG) has long been a cornerstone of diagnosis and classification in human epilepsy, but because of several technical challenges has played a smaller clinical role in canine epilepsy. The interictal (between seizures) and ictal (seizure) EEG recorded from the epileptic mammalian brain shows characteristic electrophysiologic biomarkers that are very useful for clinical management. A fundamental engineering gap for both humans and canines with epilepsy has been the challenge of obtaining continuous long-term EEG in the patients' natural environment. We are now on the cusp of a revolution where continuous long-term EEG from behaving canines and humans will be available to guide clinicians in the diagnosis and optimal treatment of their patients. Here we review some of the devices that have recently emerged for obtaining long-term EEG in ambulatory subjects living in their natural environments.
Collapse
Affiliation(s)
- Wolfgang Löscher
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine, Hanover, Germany
- Center for Systems Neuroscience, Hanover, Germany
- *Correspondence: Wolfgang Löscher
| | - Gregory A. Worrell
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States
| |
Collapse
|
13
|
Alarie ME, Provenza NR, Avendano-Ortega M, McKay SA, Waite AS, Mathura RK, Herron JA, Sheth SA, Borton DA, Goodman WK. Artifact characterization and mitigation techniques during concurrent sensing and stimulation using bidirectional deep brain stimulation platforms. Front Hum Neurosci 2022; 16:1016379. [PMID: 36337849 PMCID: PMC9626519 DOI: 10.3389/fnhum.2022.1016379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 10/03/2022] [Indexed: 11/30/2022] Open
Abstract
Bidirectional deep brain stimulation (DBS) platforms have enabled a surge in hours of recordings in naturalistic environments, allowing further insight into neurological and psychiatric disease states. However, high amplitude, high frequency stimulation generates artifacts that contaminate neural signals and hinder our ability to interpret the data. This is especially true in psychiatric disorders, for which high amplitude stimulation is commonly applied to deep brain structures where the native neural activity is miniscule in comparison. Here, we characterized artifact sources in recordings from a bidirectional DBS platform, the Medtronic Summit RC + S, with the goal of optimizing recording configurations to improve signal to noise ratio (SNR). Data were collected from three subjects in a clinical trial of DBS for obsessive-compulsive disorder. Stimulation was provided bilaterally to the ventral capsule/ventral striatum (VC/VS) using two independent implantable neurostimulators. We first manipulated DBS amplitude within safe limits (2–5.3 mA) to characterize the impact of stimulation artifacts on neural recordings. We found that high amplitude stimulation produces slew overflow, defined as exceeding the rate of change that the analog to digital converter can accurately measure. Overflow led to expanded spectral distortion of the stimulation artifact, with a six fold increase in the bandwidth of the 150.6 Hz stimulation artifact from 147–153 to 140–180 Hz. By increasing sense blank values during high amplitude stimulation, we reduced overflow by as much as 30% and improved artifact distortion, reducing the bandwidth from 140–180 Hz artifact to 147–153 Hz. We also identified artifacts that shifted in frequency through modulation of telemetry parameters. We found that telemetry ratio changes led to predictable shifts in the center-frequencies of the associated artifacts, allowing us to proactively shift the artifacts outside of our frequency range of interest. Overall, the artifact characterization methods and results described here enable increased data interpretability and unconstrained biomarker exploration using data collected from bidirectional DBS devices.
Collapse
Affiliation(s)
| | - Nicole R. Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Michelle Avendano-Ortega
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Sarah A. McKay
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Ayan S. Waite
- Brown University School of Engineering, Providence, RI, United States
| | - Raissa K. Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Jeffrey A. Herron
- Department of Neurological Surgery, University of Washington, Seattle, WA, United States
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - David A. Borton
- Brown University School of Engineering, Providence, RI, United States
- Department of Veterans Affairs, Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence, RI, United States
| | - Wayne K. Goodman
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
- *Correspondence: Wayne K. Goodman,
| |
Collapse
|
14
|
Simpson HD, Schulze-Bonhage A, Cascino GD, Fisher RS, Jobst BC, Sperling MR, Lundstrom BN. Practical considerations in epilepsy neurostimulation. Epilepsia 2022; 63:2445-2460. [PMID: 35700144 PMCID: PMC9888395 DOI: 10.1111/epi.17329] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 06/10/2022] [Accepted: 06/13/2022] [Indexed: 02/02/2023]
Abstract
Neuromodulation is a key therapeutic tool for clinicians managing patients with drug-resistant epilepsy. Multiple devices are available with long-term follow-up and real-world experience. The aim of this review is to give a practical summary of available neuromodulation techniques to guide the selection of modalities, focusing on patient selection for devices, common approaches and techniques for initiation of programming, and outpatient management issues. Vagus nerve stimulation (VNS), deep brain stimulation of the anterior nucleus of the thalamus (DBS-ANT), and responsive neurostimulation (RNS) are all supported by randomized controlled trials that show safety and a significant impact on seizure reduction, as well as a suggestion of reduction in the risk of sudden unexplained death in epilepsy (SUDEP). Significant seizure reductions are observed after 3 months for DBS, RNS, and VNS in randomized controlled trials, and efficacy appears to improve with time out to 7 to 10 years of follow-up for all modalities, albeit in uncontrolled follow-up or retrospective studies. A significant number of patients experience seizure-free intervals of 6 months or more with all three modalities. Number and location of epileptogenic foci are important factors affecting efficacy, and together with comorbidities such as severe mood or sleep disorders, may influence the choice of modality. Programming has evolved-DBS is typically initiated at lower current/voltage than used in the pivotal trial, whereas target charge density is lower with RNS, however generalizable optimal parameters are yet to be defined. Noninvasive brain stimulation is an emerging stimulation modality, although it is currently not used widely. In summary, clinical practice has evolved from those established in pivotal trials. Guidance is now available for clinicians who wish to expand their approach, and choice of neuromodulation technique may be tailored to individual patients based on their epilepsy characteristics, risk tolerance, and preferences.
Collapse
Affiliation(s)
- Hugh D. Simpson
- Division of Epilepsy, Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - Gregory D. Cascino
- Division of Epilepsy, Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Robert S. Fisher
- Department of Neurology, Stanford Neuroscience Health Center, Palo Alto, CA, USA
| | - Barbara C. Jobst
- Geisel School of Medicine at Dartmouth, Department of Neurology, Dartmouth-Hitchcock Medical Center, NH, USA
| | - Michael R. Sperling
- Division of Epilepsy, Department of Neurology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Brian N. Lundstrom
- Division of Epilepsy, Department of Neurology, Mayo Clinic, Rochester, MN, USA
| |
Collapse
|
15
|
Yang JC, Bullinger KL, Dickey AS, Karakis I, Alwaki A, Cabaniss BT, Winkel D, Rodriguez-Ruiz A, Willie JT, Gross RE. Anterior nucleus of the thalamus deep brain stimulation vs temporal lobe responsive neurostimulation for temporal lobe epilepsy. Epilepsia 2022; 63:2290-2300. [PMID: 35704344 PMCID: PMC9675907 DOI: 10.1111/epi.17331] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 06/13/2022] [Accepted: 06/14/2022] [Indexed: 11/28/2022]
Abstract
OBJECTIVE Based on the promising results of randomized controlled trials, deep brain stimulation (DBS) and responsive neurostimulation (RNS) are used increasingly in the treatment of patients with drug-resistant epilepsy. Drug-resistant temporal lobe epilepsy (TLE) is an indication for either DBS of the anterior nucleus of the thalamus (ANT) or temporal lobe (TL) RNS, but there are no studies that directly compare the seizure benefits and adverse effects associated with these therapies in this patient population. We, therefore, examined all patients who underwent ANT-DBS or TL-RNS for drug-resistant TLE at our center. METHODS We performed a retrospective review of patients who were treated with either ANT-DBS or TL-RNS for drug-resistant TLE with at least 12 months of follow-up. Along with the clinical characteristics of each patient's epilepsy, seizure frequency was recorded throughout each patient's postoperative clinical course. RESULTS Twenty-six patients underwent ANT-DBS implantation and 32 patients underwent TL-RNS for drug-resistant TLE. The epilepsy characteristics of both groups were similar. Patients who underwent ANT-DBS demonstrated a median seizure reduction of 58% at 12-15 months, compared to a median seizure reduction of 70% at 12-15 months in patients treated with TL-RNS (p > .05). The responder rate (percentage of patients with a 50% decrease or more in seizure frequency) was 54% for ANT-DBS and 56% for TL-RNS (p > .05). The incidence of complications and stimulation-related side effects did not significantly differ between therapies. SIGNIFICANCE We demonstrate in our single-center experience that patients with drug-resistant TLE benefit similarly from either ANT-DBS or TL-RNS. Selection of either ANT-DBS or TL-RNS may, therefore, depend more heavily on patient and provider preference, as each has unique capabilities and configurations. Future studies will consider subgroup analyses to determine if specific patients have greater seizure frequency reduction from one form of neuromodulation strategy over another.
Collapse
Affiliation(s)
- Jimmy C. Yang
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Katie L. Bullinger
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Adam S. Dickey
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Ioannis Karakis
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Abdulrahman Alwaki
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Brian T. Cabaniss
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Daniel Winkel
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | | | - Jon T. Willie
- Departments of Neurosurgery, Neurology, and Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Robert E. Gross
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, Georgia, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| |
Collapse
|
16
|
Charlebois CM, Anderson DN, Johnson KA, Philip BJ, Davis TS, Newman BJ, Peters AY, Arain AM, Dorval AD, Rolston JD, Butson CR. Patient-specific structural connectivity informs outcomes of responsive neurostimulation for temporal lobe epilepsy. Epilepsia 2022; 63:2037-2055. [PMID: 35560062 DOI: 10.1111/epi.17298] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 05/09/2022] [Accepted: 05/10/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Responsive neurostimulation is an effective therapy for patients with refractory mesial temporal lobe epilepsy. However, clinical outcomes are variable, few patients become seizure-free, and the optimal stimulation location is currently undefined. The aim of this study was to quantify responsive neurostimulation in the mesial temporal lobe, identify stimulation-dependent networks associated with seizure reduction, and determine if stimulation location or stimulation-dependent networks inform outcomes. METHODS We modeled patient-specific volumes of tissue activated and created probabilistic stimulation maps of local regions of stimulation across a retrospective cohort of 22 patients with mesial temporal lobe epilepsy. We then mapped the network stimulation effects by seeding tractography from the volume of tissue activated with both patient-specific and normative diffusion-weighted imaging. We identified networks associated with seizure reduction across patients using the patient-specific tractography maps and then predicted seizure reduction across the cohort. RESULTS Patient-specific stimulation-dependent connectivity was correlated with responsive neurostimulation effectiveness after cross-validation (p = .03); however, normative connectivity derived from healthy subjects was not (p = .44). Increased connectivity from the volume of tissue activated to the medial prefrontal cortex, cingulate cortex, and precuneus was associated with greater seizure reduction. SIGNIFICANCE Overall, our results suggest that the therapeutic effect of responsive neurostimulation may be mediated by specific networks connected to the volume of tissue activated. In addition, patient-specific tractography was required to identify structural networks correlated with outcomes. It is therefore likely that altered connectivity in patients with epilepsy may be associated with the therapeutic effect and that utilizing patient-specific imaging could be important for future studies. The structural networks identified here may be utilized to target stimulation in the mesial temporal lobe and to improve seizure reduction for patients treated with responsive neurostimulation.
Collapse
Affiliation(s)
- Chantel M Charlebois
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Scientific Computing & Imaging Institute, University of Utah, Salt Lake City, Utah, USA
| | - Daria Nesterovich Anderson
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA
- Department of Pharmacology & Toxicology, University of Utah, Salt Lake City, Utah, USA
| | - Kara A Johnson
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, Florida, USA
- Department of Neurology, University of Florida, Gainesville, Florida, USA
| | - Brian J Philip
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA
| | - Tyler S Davis
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA
| | - Blake J Newman
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA
| | - Angela Y Peters
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA
| | - Amir M Arain
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA
| | - Alan D Dorval
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
| | - John D Rolston
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Scientific Computing & Imaging Institute, University of Utah, Salt Lake City, Utah, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA
| | - Christopher R Butson
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, Florida, USA
- Department of Neurology, University of Florida, Gainesville, Florida, USA
- Department of Neurosurgery, University of Florida, Gainesville, Florida, USA
- Department of Biomedical Engineering, University of Florida, Gainesville, Florida, USA
| |
Collapse
|
17
|
Dastin-van Rijn EM, Provenza NR, Vogt GS, Avendano-Ortega M, Sheth SA, Goodman WK, Harrison MT, Borton DA. PELP: Accounting for Missing Data in Neural Time Series by Periodic Estimation of Lost Packets. Front Hum Neurosci 2022; 16:934063. [PMID: 35874161 PMCID: PMC9301255 DOI: 10.3389/fnhum.2022.934063] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 06/06/2022] [Indexed: 11/13/2022] Open
Abstract
Recent advances in wireless data transmission technology have the potential to revolutionize clinical neuroscience. Today sensing-capable electrical stimulators, known as "bidirectional devices", are used to acquire chronic brain activity from humans in natural environments. However, with wireless transmission come potential failures in data transmission, and not all available devices correctly account for missing data or provide precise timing for when data losses occur. Our inability to precisely reconstruct time-domain neural signals makes it difficult to apply subsequent neural signal processing techniques and analyses. Here, our goal was to accurately reconstruct time-domain neural signals impacted by data loss during wireless transmission. Towards this end, we developed a method termed Periodic Estimation of Lost Packets (PELP). PELP leverages the highly periodic nature of stimulation artifacts to precisely determine when data losses occur. Using simulated stimulation waveforms added to human EEG data, we show that PELP is robust to a range of stimulation waveforms and noise characteristics. Then, we applied PELP to local field potential (LFP) recordings collected using an implantable, bidirectional DBS platform operating at various telemetry bandwidths. By effectively accounting for the timing of missing data, PELP enables the analysis of neural time series data collected via wireless transmission-a prerequisite for better understanding the brain-behavior relationships underlying neurological and psychiatric disorders.
Collapse
Affiliation(s)
- Evan M Dastin-van Rijn
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Gregory S Vogt
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, TX, United States
| | - Michelle Avendano-Ortega
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Wayne K Goodman
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Matthew T Harrison
- Division of Applied Mathematics, Brown University, Providence, RI, United States
| | - David A Borton
- School of Engineering, Brown University, Providence, RI, United States.,Carney Institute for Brain Science, Brown University, Providence, RI, United States.,Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, United States Department of Veterans Affairs, Providence, RI, United States
| |
Collapse
|
18
|
Nowakowska M, Üçal M, Charalambous M, Bhatti SFM, Denison T, Meller S, Worrell GA, Potschka H, Volk HA. Neurostimulation as a Method of Treatment and a Preventive Measure in Canine Drug-Resistant Epilepsy: Current State and Future Prospects. Front Vet Sci 2022; 9:889561. [PMID: 35782557 PMCID: PMC9244381 DOI: 10.3389/fvets.2022.889561] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 05/23/2022] [Indexed: 11/28/2022] Open
Abstract
Modulation of neuronal activity for seizure control using various methods of neurostimulation is a rapidly developing field in epileptology, especially in treatment of refractory epilepsy. Promising results in human clinical practice, such as diminished seizure burden, reduced incidence of sudden unexplained death in epilepsy, and improved quality of life has brought neurostimulation into the focus of veterinary medicine as a therapeutic option. This article provides a comprehensive review of available neurostimulation methods for seizure management in drug-resistant epilepsy in canine patients. Recent progress in non-invasive modalities, such as repetitive transcranial magnetic stimulation and transcutaneous vagus nerve stimulation is highlighted. We further discuss potential future advances and their plausible application as means for preventing epileptogenesis in dogs.
Collapse
Affiliation(s)
- Marta Nowakowska
- Research Unit of Experimental Neurotraumatology, Department of Neurosurgery, Medical University of Graz, Graz, Austria
| | - Muammer Üçal
- Research Unit of Experimental Neurotraumatology, Department of Neurosurgery, Medical University of Graz, Graz, Austria
| | - Marios Charalambous
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hanover, Germany
| | - Sofie F. M. Bhatti
- Small Animal Department, Faculty of Veterinary Medicine, Small Animal Teaching Hospital, Ghent University, Merelbeke, Belgium
| | - Timothy Denison
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Sebastian Meller
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hanover, Germany
| | | | - Heidrun Potschka
- Faculty of Veterinary Medicine, Institute of Pharmacology, Toxicology and Pharmacy, Ludwig-Maximilians-University, Munich, Germany
| | - Holger A. Volk
- Department of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hanover, Germany
| |
Collapse
|
19
|
Sladky V, Nejedly P, Mivalt F, Brinkmann BH, Kim I, St. Louis EK, Gregg NM, Lundstrom BN, Crowe CM, Attia TP, Crepeau D, Balzekas I, Marks VS, Wheeler LP, Cimbalnik J, Cook M, Janca R, Sturges BK, Leyde K, Miller KJ, Van Gompel JJ, Denison T, Worrell GA, Kremen V. Distributed brain co-processor for tracking spikes, seizures and behavior during electrical brain stimulation. Brain Commun 2022; 4:fcac115. [PMID: 35755635 PMCID: PMC9217965 DOI: 10.1093/braincomms/fcac115] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 01/12/2022] [Accepted: 05/05/2022] [Indexed: 11/12/2022] Open
Abstract
Abstract
Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioral inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behavior and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a hand-held device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes, and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from 9 humans and 8 canines with epilepsy, and then implemented prospectively in out-of-sample testing in 2 pet canines and 4 humans with drug resistant epilepsy living in their natural environments. Accurate seizure diaries are needed as the primary clinical outcome measure of epilepsy therapy and to guide brain stimulation optimization. The brain co-processor system described here enables tracking interictal epileptiform spikes, seizures, and correlation with patient behavioral reports. In the future correlation of spikes and seizures with behavior will allow more detailed investigation of the clinical impact of spikes and seizures on patients.
Collapse
Affiliation(s)
- Vladimir Sladky
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
- International Clinical Research Center, St. Anne’s University Hospital, Brno, Czech Republic
- Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czech Republic
| | - Petr Nejedly
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
- International Clinical Research Center, St. Anne’s University Hospital, Brno, Czech Republic
- The Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czech Republic
| | - Filip Mivalt
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
- Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno, Czech Republic
| | - Benjamin H. Brinkmann
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Inyong Kim
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
| | - Erik K. St. Louis
- Center for Sleep Medicine, Departments of Neurology and Medicine, Divisions of Sleep Neurology & Pul-monary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA
| | - Nicholas M. Gregg
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
| | - Brian N. Lundstrom
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
| | - Chelsea M. Crowe
- Department of Veterinary Clinical Sciences, University of California, Davis, CA, USA
| | - Tal Pal Attia
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
| | - Daniel Crepeau
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
| | - Irena Balzekas
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, MN, USA
- Mayo Clinic School of Medicine and the Mayo Clinic Medical Scientist Training Program, MN, USA
| | - Victoria S. Marks
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, MN, USA
| | - Lydia P. Wheeler
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, MN, USA
| | - Jan Cimbalnik
- International Clinical Research Center, St. Anne’s University Hospital, Brno, Czech Republic
| | - Mark Cook
- Department of Neurology, Royal Melbourne Hospital, Melbourne, Australia
| | - Radek Janca
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
- Second Faculty of Medicine, Motol University Hospital, Charles University, Prague, Czech Republic
| | - Beverly K. Sturges
- Department of Veterinary Clinical Sciences, University of California, Davis, CA, USA
| | | | - Kai J. Miller
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, USA
| | | | | | - Gregory A. Worrell
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Vaclav Kremen
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Roch-ester, MN, USA
- Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic
| |
Collapse
|
20
|
Aungaroon G. Does Deep Brain Stimulation Work in Lennox-Gastaut Syndrome? Well…it Depends. Epilepsy Curr 2022; 22:222-224. [PMID: 36187143 PMCID: PMC9483756 DOI: 10.1177/15357597221098819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
DBS of Thalamic Centromedian Nucleus for Lennox–Gastaut Syndrome (ESTEL
Trial) Dalic LJ, Warren AEL, Bulluss KJ, Thevathasan W, et al. Ann Nuerol.
2022;91(2):253-267. doi:10.1002/ana.26280. PMID:
34877694. Objective: Prior uncontrolled studies have reported seizure reductions following deep brain
stimulation (DBS) in patients with Lennox-Gastaut syndrome (LGS), but evidence from
randomized controlled studies is lacking. We aimed to formally assess the efficacy
and safety of DBS to the centromedian thalamic nucleus (CM) for the treatment of
LGS. Methods: We conducted a prospective, double-blind, randomized study of continuous, cycling
stimulation of CM-DBS, in patients with LGS. Following pre- and post-implantation
periods, half received 3 months of stimulation (blinded phase), then all received 3
months of stimulation (unblinded phase). The primary outcome was the proportion of
participants with ≥50% reduction in diary-recorded seizures in stimulated vs control
participants, measured at the end of the blinded phase. A secondary outcome was the
proportion of participants with a ≥50% reduction in electrographic seizures on
24-hour ambulatory electroencephalography (EEG) at the end of the blinded phase. Results: Between November 2017 and December 2019, 20 young adults with LGS (17-37 years;13
women) underwent bilateral CM-DBS at a single center in Australia, with 19
randomized (treatment, n = 10 and control, n = 9). Fifty percent of the stimulation
group achieved ≥50% seizure reduction, compared with 22% of controls (odds ratio
[OR] = 3.1, 95% confidence interval [CI] = .44-21.45, P = .25). For electrographic
seizures, 59% of the stimulation group had ≥50% reduction at the end of the blinded
phase, compared with none of the controls (OR= 23.25, 95% CI = 1.0-538.4, P = .05).
Across all patients, median seizure reduction (baseline vs study exit) was 46.7%
(interquartile range [IQR] = 28-67%) for diary recorded seizures and 53.8% (IQR =
27-73%) for electrographic seizures. Interpretation: CM-DBS in patients with LGS reduced electrographic rather than diary-recorded
seizures, after 3 months of stimulation. Fifty percent of all participants had
diary-recorded seizures reduced by half at the study exit, providing supporting
evidence of the treatment effect.
Collapse
Affiliation(s)
- Gewalin Aungaroon
- Department of Neurology, College of Medicine, Cincinnati Children’s Hospital, University of Cincinnati, OH, USA
| |
Collapse
|
21
|
Low Power EEG Data Encoding for Brain Neurostimulation Implants. INFORMATION 2022. [DOI: 10.3390/info13040194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Neurostimulation devices applied for the treatment of epilepsy that collect, encode, temporarily store, and transfer electroencephalographic (EEG) signals recorded intracranially from epileptic patients, suffer from short battery life spans. The principal goal of this study is to implement strategies for low power consumption rates during the device’s smooth and uninterrupted operation as well as during data transmission. Our approach is organised in three basic levels. The first level regards the initial modelling and creation of the template for the following two stages. The second level regards the development of code for programming integrated circuits and simulation. The third and final stage regards the transmitter’s implementation at the evaluation level. In particular, more than one software and device are involved in this phase, in order to achieve realistic performance. Our research aims to evolve such technologies so that they can transmit wireless data with simultaneous energy efficiency.
Collapse
|
22
|
Wong JK, Deuschl G, Wolke R, Bergman H, Muthuraman M, Groppa S, Sheth SA, Bronte-Stewart HM, Wilkins KB, Petrucci MN, Lambert E, Kehnemouyi Y, Starr PA, Little S, Anso J, Gilron R, Poree L, Kalamangalam GP, Worrell GA, Miller KJ, Schiff ND, Butson CR, Henderson JM, Judy JW, Ramirez-Zamora A, Foote KD, Silburn PA, Li L, Oyama G, Kamo H, Sekimoto S, Hattori N, Giordano JJ, DiEuliis D, Shook JR, Doughtery DD, Widge AS, Mayberg HS, Cha J, Choi K, Heisig S, Obatusin M, Opri E, Kaufman SB, Shirvalkar P, Rozell CJ, Alagapan S, Raike RS, Bokil H, Green D, Okun MS. Proceedings of the Ninth Annual Deep Brain Stimulation Think Tank: Advances in Cutting Edge Technologies, Artificial Intelligence, Neuromodulation, Neuroethics, Pain, Interventional Psychiatry, Epilepsy, and Traumatic Brain Injury. Front Hum Neurosci 2022; 16:813387. [PMID: 35308605 PMCID: PMC8931265 DOI: 10.3389/fnhum.2022.813387] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 01/11/2022] [Indexed: 01/09/2023] Open
Abstract
DBS Think Tank IX was held on August 25-27, 2021 in Orlando FL with US based participants largely in person and overseas participants joining by video conferencing technology. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging deep brain stimulation (DBS) technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank IX speakers was that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. After collectively sharing our experiences, it was estimated that globally more than 230,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. As such, this year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia and Australia; cutting-edge technologies, neuroethics, interventional psychiatry, adaptive DBS, neuromodulation for pain, network neuromodulation for epilepsy and neuromodulation for traumatic brain injury.
Collapse
Affiliation(s)
- Joshua K. Wong
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Günther Deuschl
- Department of Neurology, Christian-Albrechts-University, Kiel, Germany
| | - Robin Wolke
- Department of Neurology, Christian-Albrechts-University, Kiel, Germany
| | - Hagai Bergman
- Department of Medical Neurobiology (Physiology), Institute of Medical Research Israel-Canada, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Muthuraman Muthuraman
- Biomedical Statistics and Multimodal Signal Processing Unit, Section of Movement Disorders and Neurostimulation, Focus Program Translational Neuroscience, Department of Neurology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Biomedical Statistics and Multimodal Signal Processing Unit, Section of Movement Disorders and Neurostimulation, Focus Program Translational Neuroscience, Department of Neurology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sameer A. Sheth
- Department of Neurological Surgery, Baylor College of Medicine, Houston, TX, United States
| | - Helen M. Bronte-Stewart
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
| | - Kevin B. Wilkins
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
| | - Matthew N. Petrucci
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
| | - Emilia Lambert
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
| | - Yasmine Kehnemouyi
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
| | - Philip A. Starr
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Simon Little
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Juan Anso
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Ro’ee Gilron
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Lawrence Poree
- Department of Anesthesia, University of California, San Francisco, San Francisco, CA, United States
| | - Giridhar P. Kalamangalam
- Department of Neurology, Wilder Center for Epilepsy Research, University of Florida, Gainesville, FL, United States
| | | | - Kai J. Miller
- Department of Neurosurgery, Mayo Clinic, Rochester, NY, United States
| | - Nicholas D. Schiff
- Department of Neurology, Weill Cornell Brain and Spine Institute, Weill Cornell Medicine, New York, NY, United States
| | - Christopher R. Butson
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Jaimie M. Henderson
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
| | - Jack W. Judy
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States
| | - Adolfo Ramirez-Zamora
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Kelly D. Foote
- Department of Neurosurgery, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Peter A. Silburn
- Queensland Brain Institute, University of Queensland and Saint Andrews War Memorial Hospital, Brisbane, QLD, Australia
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Genko Oyama
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Hikaru Kamo
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Satoko Sekimoto
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - Nobutaka Hattori
- Department of Neurology, Faculty of Medicine, Juntendo University, Tokyo, Japan
| | - James J. Giordano
- Neuroethics Studies Program, Department of Neurology, Georgetown University Medical Center, Washington, DC, United States
| | - Diane DiEuliis
- US Department of Defense Fort Lesley J. McNair, National Defense University, Washington, DC, United States
| | - John R. Shook
- Department of Philosophy and Science Education, University of Buffalo, Buffalo, NY, United States
| | - Darin D. Doughtery
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Alik S. Widge
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, United States
| | - Helen S. Mayberg
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Jungho Cha
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Kisueng Choi
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Stephen Heisig
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Mosadolu Obatusin
- Department of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Enrico Opri
- Department of Neurology, Emory University, Atlanta, GA, United States
| | - Scott B. Kaufman
- Department of Psychology, Columbia University, New York, NY, United States
| | - Prasad Shirvalkar
- The Human Motor Control and Neuromodulation Laboratory, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford University, Stanford, CA, United States
- Department of Anesthesiology (Pain Management) and Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Christopher J. Rozell
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Sankaraleengam Alagapan
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States
| | - Robert S. Raike
- Restorative Therapies Group Implantables, Research and Core Technology, Medtronic Inc., Minneapolis, MN, United States
| | - Hemant Bokil
- Boston Scientific Neuromodulation Corporation, Valencia, CA, United States
| | - David Green
- NeuroPace, Inc., Mountain View, CA, United States
| | - Michael S. Okun
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| |
Collapse
|
23
|
Richardson RM. Closed-Loop Brain Stimulation and Paradigm Shifts in Epilepsy Surgery. Neurol Clin 2022; 40:355-373. [PMID: 35465880 PMCID: PMC9271409 DOI: 10.1016/j.ncl.2021.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Advances in device technology have created greater flexibility in treating seizures as emergent properties of networks that exist on a local to global continuum. All patients with drug-resistant epilepsy are potential surgical candidates, given that intracranial neuromodulation through deep brain stimulation and responsive neurostimulation can reduce seizures and improve quality of life, even in multifocal and generalized epilepsies. To achieve this goal, indications and strategies for diagnostic epilepsy surgery are evolving. This article describes the state-of-the-art in epilepsy surgery and related changes in how we define indications for diagnostic and therapeutic surgical intervention.
Collapse
|
24
|
Vetkas A, Fomenko A, Germann J, Sarica C, Iorio-Morin C, Samuel N, Yamamoto K, Milano V, Cheyuo C, Zemmar A, Elias G, Boutet A, Loh A, Santyr B, Gwun D, Tasserie J, Kalia SK, Lozano AM. Deep brain stimulation targets in epilepsy: Systematic review and meta-analysis of anterior and centromedian thalamic nuclei and hippocampus. Epilepsia 2022; 63:513-524. [PMID: 34981509 DOI: 10.1111/epi.17157] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 12/13/2021] [Accepted: 12/13/2021] [Indexed: 12/11/2022]
Abstract
Deep brain stimulation (DBS) is a neuromodulatory treatment used in patients with drug-resistant epilepsy (DRE). The primary goal of this systematic review and meta-analysis is to describe recent advancements in the field of DBS for epilepsy, to compare the results of published trials, and to clarify the clinical utility of DBS in DRE. A systematic literature search was performed by two independent authors. Forty-four articles were included in the meta-analysis (23 for anterior thalamic nucleus [ANT], 8 for centromedian thalamic nucleus [CMT], and 13 for hippocampus) with a total of 527 patients. The mean seizure reduction after stimulation of the ANT, CMT, and hippocampus in our meta-analysis was 60.8%, 73.4%, and 67.8%, respectively. DBS is an effective and safe therapy in patients with DRE. Based on the results of randomized controlled trials and larger clinical series, the best evidence exists for DBS of the anterior thalamic nucleus. Further randomized trials are required to clarify the role of CMT and hippocampal stimulation. Our analysis suggests more efficient deep brain stimulation of ANT for focal seizures, wider use of CMT for generalized seizures, and hippocampal DBS for temporal lobe seizures. Factors associated with clinical outcome after DBS for epilepsy are electrode location, stimulation parameters, type of epilepsy, and longer time of stimulation. Recent advancements in anatomical targeting, functional neuroimaging, responsive neurostimulation, and sensing of local field potentials could potentially lead to improved outcomes after DBS for epilepsy and reduced sudden, unexpected death of patients with epilepsy. Biomarkers are needed for successful patient selection, targeting of electrodes and optimization of stimulation parameters.
Collapse
Affiliation(s)
- Artur Vetkas
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.,Neurology Clinic, Department of Neurosurgery, Tartu University Hospital, University of Tartu, Tartu, Estonia
| | - Anton Fomenko
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.,Section of Neurosurgery, Health Sciences Centre, University of Manitoba, Winnipeg, MB, Canada
| | - Jürgen Germann
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Can Sarica
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Christian Iorio-Morin
- Division of Neurosurgery, Centre de recherché du CHUS, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Nardin Samuel
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Kazuaki Yamamoto
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Vanessa Milano
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Cletus Cheyuo
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Ajmal Zemmar
- Department of Neurosurgery, University of Louisville, School of Medicine, Louisville, KY, USA
| | - Gavin Elias
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Alexandre Boutet
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.,Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Aaron Loh
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Brendan Santyr
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.,Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Dave Gwun
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Jordy Tasserie
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Suneil K Kalia
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.,Krembil Research Institute, Toronto, ON, Canada
| | - Andres M Lozano
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.,Krembil Research Institute, Toronto, ON, Canada
| |
Collapse
|
25
|
Gregg NM, Sladky V, Nejedly P, Mivalt F, Kim I, Balzekas I, Sturges BK, Crowe C, Patterson EE, Van Gompel JJ, Lundstrom BN, Leyde K, Denison TJ, Brinkmann BH, Kremen V, Worrell GA. Thalamic deep brain stimulation modulates cycles of seizure risk in epilepsy. Sci Rep 2021; 11:24250. [PMID: 34930926 PMCID: PMC8688461 DOI: 10.1038/s41598-021-03555-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 12/03/2021] [Indexed: 11/30/2022] Open
Abstract
Chronic brain recordings suggest that seizure risk is not uniform, but rather varies systematically relative to daily (circadian) and multiday (multidien) cycles. Here, one human and seven dogs with naturally occurring epilepsy had continuous intracranial EEG (median 298 days) using novel implantable sensing and stimulation devices. Two pet dogs and the human subject received concurrent thalamic deep brain stimulation (DBS) over multiple months. All subjects had circadian and multiday cycles in the rate of interictal epileptiform spikes (IES). There was seizure phase locking to circadian and multiday IES cycles in five and seven out of eight subjects, respectively. Thalamic DBS modified circadian (all 3 subjects) and multiday (analysis limited to the human participant) IES cycles. DBS modified seizure clustering and circadian phase locking in the human subject. Multiscale cycles in brain excitability and seizure risk are features of human and canine epilepsy and are modifiable by thalamic DBS.
Collapse
Affiliation(s)
- Nicholas M Gregg
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Rochester, MN, 55905, USA.
| | - Vladimir Sladky
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Rochester, MN, 55905, USA
- International Clinical Research Center, St. Anne's University Hospital, 656 91, Brno, Czech Republic
- Faculty of Biomedical Engineering, Czech Technical University in Prague, 272 01, Kladno, Czech Republic
| | - Petr Nejedly
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Rochester, MN, 55905, USA
- International Clinical Research Center, St. Anne's University Hospital, 656 91, Brno, Czech Republic
| | - Filip Mivalt
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Rochester, MN, 55905, USA
- International Clinical Research Center, St. Anne's University Hospital, 656 91, Brno, Czech Republic
- Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, 616 00, Brno, Czech Republic
| | - Inyong Kim
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Rochester, MN, 55905, USA
| | - Irena Balzekas
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Rochester, MN, 55905, USA
- Mayo Clinic School of Medicine and the Medical Scientist Training Program, Mayo Clinic, Rochester, MN, 55905, USA
| | - Beverly K Sturges
- Department of Veterinary Clinical Sciences, University of California, Davis, CA, 95616, USA
| | - Chelsea Crowe
- Department of Veterinary Clinical Sciences, University of California, Davis, CA, 95616, USA
| | - Edward E Patterson
- Department of Veterinary Clinical Sciences, University of Minnesota College of Veterinary Medicine, St. Paul, MN, 55108, USA
| | | | - Brian N Lundstrom
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Rochester, MN, 55905, USA
| | - Kent Leyde
- Cadence Neuroscience, Seattle, WA, 98052, USA
| | - Timothy J Denison
- Institute for Biomedical Engineering, Oxford University, Oxford, OX3 7DQ, UK
| | - Benjamin H Brinkmann
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Rochester, MN, 55905, USA
| | - Vaclav Kremen
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Rochester, MN, 55905, USA
- Czech Institute of Informatics, Robotics, and Cybernetics, Czech Technical University in Prague, 160 00, Prague, Czech Republic
| | - Gregory A Worrell
- Department of Neurology, Bioelectronics Neurophysiology and Engineering Laboratory, Mayo Clinic, Rochester, MN, 55905, USA.
| |
Collapse
|
26
|
Rao VR. Chronic electroencephalography in epilepsy with a responsive neurostimulation device: current status and future prospects. Expert Rev Med Devices 2021; 18:1093-1105. [PMID: 34696676 DOI: 10.1080/17434440.2021.1994388] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
INTRODUCTION Implanted neurostimulation devices are gaining traction as therapeutic options for people with certain forms of drug-resistant focal epilepsy. Some of these devices enable chronic electroencephalography (cEEG), which offers views of the dynamics of brain activity in epilepsy over unprecedented time horizons. AREAS COVERED This review focuses on clinical insights and basic neuroscience discoveries enabled by analyses of cEEG from an exemplar device, the NeuroPace RNS® System. Applications of RNS cEEG covered here include counting and lateralizing seizures, quantifying medication response, characterizing spells, forecasting seizures, and exploring mechanisms of cognition. Limitations of the RNS System are discussed in the context of next-generation devices in development. EXPERT OPINION The wide temporal lens of cEEG helps capture the dynamism of epilepsy, revealing phenomena that cannot be appreciated with short duration recordings. The RNS System is a vanguard device whose diagnostic utility rivals its therapeutic benefits, but emerging minimally invasive devices, including those with subscalp recording electrodes, promise to be more applicable within a broad population of people with epilepsy. Epileptology is on the precipice of a paradigm shift in which cEEG is a standard part of diagnostic evaluations and clinical management is predicated on quantitative observations integrated over long timescales.
Collapse
Affiliation(s)
- Vikram R Rao
- Associate Professor of Clinical Neurology, Chief, Epilepsy Division, Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| |
Collapse
|