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Johnson KA, Dosenbach NUF, Gordon EM, Welle CG, Wilkins KB, Bronte-Stewart HM, Voon V, Morishita T, Sakai Y, Merner AR, Lázaro-Muñoz G, Williamson T, Horn A, Gilron R, O'Keeffe J, Gittis AH, Neumann WJ, Little S, Provenza NR, Sheth SA, Fasano A, Holt-Becker AB, Raike RS, Moore L, Pathak YJ, Greene D, Marceglia S, Krinke L, Tan H, Bergman H, Pötter-Nerger M, Sun B, Cabrera LY, McIntyre CC, Harel N, Mayberg HS, Krystal AD, Pouratian N, Starr PA, Foote KD, Okun MS, Wong JK. Proceedings of the 11th Annual Deep Brain Stimulation Think Tank: pushing the forefront of neuromodulation with functional network mapping, biomarkers for adaptive DBS, bioethical dilemmas, AI-guided neuromodulation, and translational advancements. Front Hum Neurosci 2024; 18:1320806. [PMID: 38450221 PMCID: PMC10915873 DOI: 10.3389/fnhum.2024.1320806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/05/2024] [Indexed: 03/08/2024] Open
Abstract
The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9-11, 2023 in Gainesville, Florida with the theme of "Pushing the Forefront of Neuromodulation". The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic DBS. 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 DBS technologies, as well as logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices.
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Affiliation(s)
- Kara A. Johnson
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Nico U. F. Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Evan M. Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Cristin G. Welle
- Department of Physiology and Biophysics, University of Colorado School of Medicine, Aurora, CO, United States
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, CO, United States
| | - Kevin B. Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Helen M. Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Takashi Morishita
- Department of Neurosurgery, Fukuoka University Faculty of Medicine, Fukuoka, Japan
| | - Yuki Sakai
- ATR Brain Information Communication Research Laboratory Group, Kyoto, Japan
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Amanda R. Merner
- Center for Bioethics, Harvard Medical School, Boston, MA, United States
| | - Gabriel Lázaro-Muñoz
- Center for Bioethics, Harvard Medical School, Boston, MA, United States
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
| | - Theresa Williamson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, United States
| | - Andreas Horn
- Department of Neurology, Center for Brain Circuit Therapeutics, Harvard Medical School, Brigham & Women's Hospital, Boston, MA, United States
- MGH Neurosurgery and Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Berlin, Germany
| | | | | | - Aryn H. Gittis
- Biological Sciences and Center for Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Berlin, Germany
| | - Simon Little
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Nicole R. Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Alfonso Fasano
- Edmond J. Safra Program in Parkinson's Disease, Division of Neurology, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network (UHN), University of Toronto, Toronto, ON, Canada
- Krembil Brain Institute, Toronto, ON, Canada
| | - Abbey B. Holt-Becker
- Restorative Therapies Group Implantables, Research, and Core Technology, Medtronic Inc., Minneapolis, MN, United States
| | - Robert S. Raike
- Restorative Therapies Group Implantables, Research, and Core Technology, Medtronic Inc., Minneapolis, MN, United States
| | - Lisa Moore
- Boston Scientific Neuromodulation Corporation, Valencia, CA, United States
| | | | - David Greene
- NeuroPace, Inc., Mountain View, CA, United States
| | - Sara Marceglia
- Department of Engineering and Architecture, University of Trieste, Trieste, Italy
| | - Lothar Krinke
- Newronika SPA, Milan, Italy
- Department of Neuroscience, West Virginia University, Morgantown, WV, United States
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Hagai Bergman
- Edmond and Lily Safar Center (ELSC) for Brain Research and Department of Medical Neurobiology (Physiology), Institute of Medical Research Israel-Canada, Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Neurosurgery, Hadassah Medical Center, Jerusalem, Israel
| | - Monika Pötter-Nerger
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Bomin Sun
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Laura Y. Cabrera
- Neuroethics, Department of Engineering Science and Mechanics, Philosophy, and Bioethics, and the Rock Ethics Institute, Pennsylvania State University, State College, PA, United States
| | - Cameron C. McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
- Department of Neurosurgery, Duke University, Durham, NC, United States
| | - Noam Harel
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Helen S. Mayberg
- Department of Neurology, Neurosurgery, Psychiatry, and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Andrew D. Krystal
- Departments of Psychiatry and Behavioral Science and Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Nader Pouratian
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Philip A. Starr
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Kelly D. Foote
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, University of Florida, Gainesville, FL, United States
| | - Michael S. Okun
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Joshua K. Wong
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurology, University of Florida, Gainesville, FL, United States
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Wolke R, Becktepe JS, Paschen S, Helmers A, Kübler‐Weller D, Youn J, Brinker D, Bergman H, Kühn AA, Fasano A, Deuschl G. The Role of Levodopa Challenge in Predicting the Outcome of Subthalamic Deep Brain Stimulation. Mov Disord Clin Pract 2023; 10:1181-1191. [PMID: 37635781 PMCID: PMC10450242 DOI: 10.1002/mdc3.13825] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 05/14/2023] [Accepted: 06/14/2023] [Indexed: 08/29/2023] Open
Abstract
Background Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective and evidence-based treatment for idiopathic Parkinson's disease (iPD). A minority of patients does not sufficiently benefit from STN-DBS. Objective The predictive validity of the levodopa challenge for individual patients is analyzed. Methods Data from patients assessed with a preoperative Levodopa-test and a follow-up examination (mean ± standard deviation: 9.15 months ±3.39) from Kiel (n = 253), Berlin (n = 78) and Toronto (n = 98) were studied. Insufficient DBS outcome was defined as an overall UPDRS-III reduction <33% compared to UPDRS-III in med-off at baseline or alternatively if the minimal clinically important improvement of 5 points was not reached. Single UPDRS-items and sub-scores were dichotomized. Following exploratory analysis, we trained supervised regression- and classification models for outcome prediction. Results Data analysis confirmed significant correlation between the absolute UPDRS-III reduction during Levodopa challenge and after stimulation. But individual improvement was inaccurately predicted with a large range of up to 30 UPDRS III points. Further analysis identified preoperative UPDRS-III/med-off-scores and preoperative Levodopa-improvement as most influential factors. The models for UPDRS-III and sub-scores improvement achieved comparably low accuracy. Conclusions With large prediction intervals, the Levodopa challenge use for patient counseling is limited, though remains important for excluding non-responders to Levodopa. Despite these deficiencies, the current practice of patient selection is highly successful and builds not only on the Levodopa challenge. However, more specific motor tasks and further paraclinical tools for prediction need to be developed.
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Affiliation(s)
- Robin Wolke
- Department of NeurologyUKSH, Christian‐Albrechts University KielKielGermany
| | | | - Steffen Paschen
- Department of NeurologyUKSH, Christian‐Albrechts University KielKielGermany
| | - Ann‐Kristin Helmers
- Department of NeurosurgeryUKSH, Christian‐Albrechts University KielKielGermany
| | - Dorothee Kübler‐Weller
- Movement Disorder and Neuromodulation Unit, Department of NeurologyCharité–UniversitätsmedizinBerlinGermany
| | - Jinyoung Youn
- Department of Neurology, Samsung Medical CenterSchool of medicine Sungkyunkwan UniversitySeoulSouth Korea
| | - Dana Brinker
- Department of NeurologyUKSH, Christian‐Albrechts University KielKielGermany
| | - Hagai Bergman
- The Edmond andLily Safra Center for Brain Sciences (ELSC)The Hebrew UniversityJerusalemIsrael
- Department of Medical Neurobiology (Physiology), Institute of Medical Research‐Israel Canada (IMRIC), Faculty of MedicineThe Hebrew UniversityJerusalemIsrael
- Department of Neurosurgery, Hadassah Medical CenterThe Hebrew UniversityJerusalemIsrael
| | - Andrea A. Kühn
- Movement Disorder and Neuromodulation Unit, Department of NeurologyCharité–UniversitätsmedizinBerlinGermany
| | - Alfonso Fasano
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders ClinicToronto Western Hospital, UHNTorontoOntarioCanada
- Division of NeurologyUniversity of TorontoTorontoOntarioCanada
- Krembil Brain InstituteTorontoOntarioCanada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA)TorontoOntarioCanada
| | - Günther Deuschl
- Department of NeurologyUKSH, Christian‐Albrechts University KielKielGermany
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Guerra A, D'Onofrio V, Ferreri F, Bologna M, Antonini A. Objective measurement versus clinician-based assessment for Parkinson's disease. Expert Rev Neurother 2023; 23:689-702. [PMID: 37366316 DOI: 10.1080/14737175.2023.2229954] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 06/18/2023] [Accepted: 06/22/2023] [Indexed: 06/28/2023]
Abstract
INTRODUCTION Although clinician-based assessment through standardized clinical rating scales is currently the gold standard for quantifying motor impairment in Parkinson's disease (PD), it is not without limitations, including intra- and inter-rater variability and a degree of approximation. There is increasing evidence supporting the use of objective motion analyses to complement clinician-based assessment. Objective measurement tools hold significant potential for improving the accuracy of clinical and research-based evaluations of patients. AREAS COVERED The authors provide several examples from the literature demonstrating how different motion measurement tools, including optoelectronics, contactless and wearable systems allow for both the objective quantification and monitoring of key motor symptoms (such as bradykinesia, rigidity, tremor, and gait disturbances), and the identification of motor fluctuations in PD patients. Furthermore, they discuss how, from a clinician's perspective, objective measurements can help in various stages of PD management. EXPERT OPINION In our opinion, sufficient evidence supports the assertion that objective monitoring systems enable accurate evaluation of motor symptoms and complications in PD. A range of devices can be utilized not only to support diagnosis but also to monitor motor symptom during the disease progression and can become relevant in the therapeutic decision-making process.
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Affiliation(s)
- Andrea Guerra
- Parkinson and Movement Disorder Unit, Study Center on Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
| | | | - Florinda Ferreri
- Unit of Neurology, Unit of Clinical Neurophysiology, Study Center of Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
- Department of Clinical Neurophysiology, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
| | - Matteo Bologna
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Angelo Antonini
- Parkinson and Movement Disorder Unit, Study Center on Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
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Roediger J, Dembek TA, Achtzehn J, Busch JL, Krämer AP, Faust K, Schneider GH, Krause P, Horn A, Kühn AA. Automated deep brain stimulation programming based on electrode location: a randomised, crossover trial using a data-driven algorithm. Lancet Digit Health 2023; 5:e59-e70. [PMID: 36528541 DOI: 10.1016/s2589-7500(22)00214-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 09/22/2022] [Accepted: 11/01/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in controlling motor symptoms in patients with Parkinson's disease. However, correct selection of stimulation parameters is pivotal to treatment success and currently follows a time-consuming and demanding trial-and-error process. We aimed to assess treatment effects of stimulation parameters suggested by a recently published algorithm (StimFit) based on neuroimaging data. METHODS This double-blind, randomised, crossover, non-inferiority trial was carried out at Charité - Universitätsmedizin, Berlin, Germany, and enrolled patients with Parkinson's disease treated with directional octopolar electrodes targeted at the STN. All patients had undergone DBS programming according to our centre's standard of care (SoC) treatment before study recruitment. Based on perioperative imaging data, DBS electrodes were reconstructed and StimFit was applied to suggest optimal stimulation settings. Patients underwent motor assessments using the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) during OFF-medication and in OFF-stimulation and ON-stimulation states under both conditions, StimFit and SoC parameter settings. Patients were randomly assigned (1:1) to receive either StimFit-programmed DBS first and SoC-programmed DBS second, or SoC-programmed DBS first and StimFit-programmed DBS second. The allocation schedule was generated using a computerised random number generator. Both the rater and patients were masked to the sequence of SoC and StimFit stimulation conditions. All patients who participated in the study were included in the analysis. The primary endpoint of this study was the absolute mean difference between MDS-UPDRS-III scores under StimFit and SoC stimulation, with a non-inferiority margin of 5 points. The study was registered at the German Register for Clinical Trials (DRKS00023115), and is complete. FINDINGS Between July 10, 2020, and Oct 28, 2021, 35 patients were enrolled in the study; 18 received StimFit followed by SoC stimulation, and 17 received SoC followed by StimFit stimulation. Mean MDS-UPDRS-III scores improved from 47·3 (SD 17·1) at OFF-stimulation baseline to 24·7 (SD 12·4) and 26·3 (SD 12·4) under SoC and StimFit stimulation, respectively. Mean difference between motor scores was -1·6 (SD 7·1; 95% CI -4·0 to 0·9; superiority test psuperiority=0·20; n=35), establishing non-inferiority of StimFit stimulation at a margin of -5 points (non-inferiority test pnon-inferiority=0·0038). In six patients (17%), initial programming of StimFit settings resulted in acute side-effects and amplitudes were reduced until side-effects disappeared. INTERPRETATION Automated data-driven algorithms can predict stimulation parameters that lead to motor symptom control comparable to SoC treatment. This approach could significantly decrease the time necessary to obtain optimal treatment parameters. FUNDING Deutsche Forschungsgemeinschaft through NeuroCure Clinical Research Center and TRR 295.
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Affiliation(s)
- Jan Roediger
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Till A Dembek
- Department of Neurology, Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Johannes Achtzehn
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Johannes L Busch
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Anna-Pauline Krämer
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Katharina Faust
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Gerd-Helge Schneider
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Patricia Krause
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Andreas Horn
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Center for Brain Circuit Therapeutics, Department of Neurology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA; MGH Neurosurgery and Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrea A Kühn
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; NeuroCure Clinical Research Centre, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; DZNE, German Center for Degenerative Diseases, Berlin, Germany.
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Wong JK, Mayberg HS, Wang DD, Richardson RM, Halpern CH, Krinke L, Arlotti M, Rossi L, Priori A, Marceglia S, Gilron R, Cavanagh JF, Judy JW, Miocinovic S, Devergnas AD, Sillitoe RV, Cernera S, Oehrn CR, Gunduz A, Goodman WK, Petersen EA, Bronte-Stewart H, Raike RS, Malekmohammadi M, Greene D, Heiden P, Tan H, Volkmann J, Voon V, Li L, Sah P, Coyne T, Silburn PA, Kubu CS, Wexler A, Chandler J, Provenza NR, Heilbronner SR, Luciano MS, Rozell CJ, Fox MD, de Hemptinne C, Henderson JM, Sheth SA, Okun MS. Proceedings of the 10th annual deep brain stimulation think tank: Advances in cutting edge technologies, artificial intelligence, neuromodulation, neuroethics, interventional psychiatry, and women in neuromodulation. Front Hum Neurosci 2023; 16:1084782. [PMID: 36819295 PMCID: PMC9933515 DOI: 10.3389/fnhum.2022.1084782] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 12/12/2022] [Indexed: 02/05/2023] Open
Abstract
The deep brain stimulation (DBS) Think Tank X was held on August 17-19, 2022 in Orlando FL. The session organizers and moderators were all women with the theme women in neuromodulation. Dr. Helen Mayberg from Mt. Sinai, NY was the keynote speaker. She discussed milestones and her experiences in developing depression DBS. 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 DBS technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank X speakers was that DBS has continued to expand in scope however several indications have reached the "trough of disillusionment." DBS for depression was considered as "re-emerging" and approaching a slope of enlightenment. DBS for depression will soon re-enter clinical trials. The group estimated that globally more than 244,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia, and Australia; cutting-edge technologies, closed loop DBS, DBS tele-health, neuroethics, lesion therapy, interventional psychiatry, and adaptive DBS.
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Affiliation(s)
- Joshua K. Wong
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
| | - Helen S. Mayberg
- Department of Neurology, Neurosurgery, Psychiatry, and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Doris D. Wang
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - R. Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Casey H. Halpern
- Richards Medical Research Laboratories, Department of Neurosurgery, Perelman School of Medicine, Pennsylvania Hospital, University of Pennsylvania, Philadelphia, PA, United States
| | - Lothar Krinke
- Newronika, Goose Creek, SC, United States
- Department of Neuroscience, West Virginia University, Morgantown, WV, United States
| | | | | | | | | | | | - James F. Cavanagh
- Department of Psychology, University of New Mexico, Albuquerque, NM, United States
| | - Jack W. Judy
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States
| | - Svjetlana Miocinovic
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, United States
| | - Annaelle D. Devergnas
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, United States
| | - Roy V. Sillitoe
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
| | - Stephanie Cernera
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Carina R. Oehrn
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Aysegul Gunduz
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States
| | - Wayne K. Goodman
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Erika A. Petersen
- Department of Neurosurgery, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Helen Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Robert S. Raike
- Restorative Therapies Group Implantables, Research, and Core Technology, Medtronic Inc., Minneapolis, MN, United States
| | | | - David Greene
- NeuroPace, Inc., Mountain View, CA, United States
| | - Petra Heiden
- Department of Stereotactic and Functional Neurosurgery, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jens Volkmann
- Department of Neurology, University of Würzburg, Würzburg, Germany
| | - Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Luming Li
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Pankaj Sah
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
| | - Terry Coyne
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
| | - Peter A. Silburn
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
| | - Cynthia S. Kubu
- Department of Neurology, Cleveland Clinic, Cleveland, OH, United States
| | - Anna Wexler
- Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia, PA, United States
| | - Jennifer Chandler
- Centre for Health Law, Policy, and Ethics, Faculty of Law, University of Ottawa, Ottawa, ON, Canada
| | - Nicole R. Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Sarah R. Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States
| | - Marta San Luciano
- Department of Neurology, Weill Institute for Neurosciences, 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
| | - Michael D. Fox
- Center for Brain Circuit Therapeutics, Department of Neurology, Psychiatry, Radiology, and Neurosurgery, Brigham and Women’s Hospital, Boston, MA, United States
| | - Coralie de Hemptinne
- 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
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Michael S. Okun
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
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Gülke E, Juárez Paz L, Scholtes H, Gerloff C, Kühn AA, Pötter-Nerger M. Multiple input algorithm-guided Deep Brain stimulation-programming for Parkinson's disease patients. NPJ Parkinsons Dis 2022; 8:144. [PMID: 36309508 PMCID: PMC9617933 DOI: 10.1038/s41531-022-00396-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 09/14/2022] [Indexed: 12/04/2022] Open
Abstract
Technological advances of Deep Brain Stimulation (DBS) within the subthalamic nucleus (STN) for Parkinson's disease (PD) provide increased programming options with higher programming burden. Reducing the effort of DBS optimization requires novel programming strategies. The objective of this study was to evaluate the feasibility of a semi-automatic algorithm-guided-programming (AgP) approach to obtain beneficial stimulation settings for PD patients with directional DBS systems. The AgP evaluates iteratively the weighted combination of sensor and clinician assessed responses of multiple PD symptoms to suggested DBS settings until it converges to a final solution. Acute clinical effectiveness of AgP DBS settings and DBS settings that were found following a standard of care (SoC) procedure were compared in a randomized, crossover and double-blind fashion in 10 PD subjects from a single center. Compared to therapy absence, AgP and SoC DBS settings significantly improved (p = 0.002) total Unified Parkinson's Disease Rating Scale III scores (median 69.8 interquartile range (IQR) 64.6|71.9% and 66.2 IQR 58.1|68.2%, respectively). Despite their similar clinical results, AgP and SoC DBS settings differed substantially. Per subject, AgP tested 37.0 IQR 34.0|37 settings before convergence, resulting in 1.7 IQR 1.6|2.0 h, which is comparable to previous reports. Although AgP long-term clinical results still need to be investigated, this approach constitutes an alternative for DBS programming and represents an important step for future closed-loop DBS optimization systems.
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Affiliation(s)
- Eileen Gülke
- grid.13648.380000 0001 2180 3484Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - León Juárez Paz
- grid.418905.10000 0004 0437 5539Boston Scientific, Valencia, CA Spain
| | - Heleen Scholtes
- grid.418905.10000 0004 0437 5539Boston Scientific, Valencia, CA Spain
| | - Christian Gerloff
- grid.13648.380000 0001 2180 3484Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Andrea A. Kühn
- grid.6363.00000 0001 2218 4662Department of Neurology, Movement disorders & Neuromodulation section, Charité – University Medicine Berlin, Berlin, Germany
| | - Monika Pötter-Nerger
- grid.13648.380000 0001 2180 3484Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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7
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Butenko K, Li N, Neudorfer C, Roediger J, Horn A, Wenzel GR, Eldebakey H, Kühn AA, Reich MM, Volkmann J, Rienen UV. Linking profiles of pathway activation with clinical motor improvements - A retrospective computational study. Neuroimage Clin 2022; 36:103185. [PMID: 36099807 PMCID: PMC9474565 DOI: 10.1016/j.nicl.2022.103185] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 07/27/2022] [Accepted: 09/02/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Deep brain stimulation (DBS) is an established therapy for patients with Parkinson's disease. In silico computer models for DBS hold the potential to inform a selection of stimulation parameters. In recent years, the focus has shifted towards DBS-induced firing in myelinated axons, deemed particularly relevant for the external modulation of neural activity. OBJECTIVE The aim of this project was to investigate correlations between patient-specific pathway activation profiles and clinical motor improvement. METHODS We used the concept of pathway activation modeling, which incorporates advanced volume conductor models and anatomically authentic fiber trajectories to estimate DBS-induced action potential initiation in anatomically plausible pathways that traverse in close proximity to targeted nuclei. We applied the method on two retrospective datasets of DBS patients, whose clinical improvement had been evaluated according to the motor part of the Unified Parkinson's Disease Rating Scale. Based on differences in outcome and activation levels for intrapatient DBS protocols in a training cohort, we derived a pathway activation profile that theoretically induces a complete alleviation of symptoms described by UPDRS-III. The profile was further enhanced by analyzing the importance of matching activation levels for individual pathways. RESULTS The obtained profile emphasized the importance of activation in pathways descending from the motor-relevant cortical regions as well as the pallidothalamic pathways. The degree of similarity of patient-specific profiles to the optimal profile significantly correlated with clinical motor improvement in a test cohort. CONCLUSION Pathway activation modeling has a translational utility in the context of motor symptom alleviation in Parkinson's patients treated with DBS.
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Affiliation(s)
- Konstantin Butenko
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany,Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany,Corresponding author.
| | - Ningfei Li
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Clemens Neudorfer
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Jan Roediger
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany,Einstein Center for Neurosciences, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Andreas Horn
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Gregor R. Wenzel
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Hazem Eldebakey
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Andrea A. Kühn
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Martin M. Reich
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Jens Volkmann
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Ursula van Rienen
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany,Department Life, Light & Matter, University of Rostock, Rostock, Germany,Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany,Corresponding author.
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8
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Sarikhani P, Ferleger B, Mitchell K, Ostrem J, Herron J, Mahmoudi B, Miocinovic S. Automated deep brain stimulation programming with safety constraints for tremor suppression in patients with Parkinson's Disease and essential tremor. J Neural Eng 2022; 19. [PMID: 35921806 DOI: 10.1088/1741-2552/ac86a2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 08/03/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVES Deep brain stimulation programming for movement disorders requires systematic fine tuning of stimulation parameters to ameliorate tremor and other symptoms while avoiding side effects. DBS programming can be a time-consuming process and requires clinical expertise to assess response to DBS to optimize therapy for each patient. In this study, we describe and evaluate an automated, closed-loop, and patient-specific framework for DBS programming that measures tremor using a smartwatch and automatically changes DBS parameters based on the recommendations from a closed-loop optimization algorithm thus eliminating the need for an expert clinician. APPROACH Bayesian optimization which is a sample-efficient global optimization method was used as the core of this DBS programming framework to adaptively learn each patient's response to DBS and suggest the next best settings to be evaluated. Input from a clinician was used initially to define a maximum safe amplitude, but we also implemented 'safe Bayesian optimization' to automatically discover tolerable exploration boundaries. RESULTS We tested the system in 15 patients (9 with Parkinson's disease and 6 with essential tremor). Tremor suppression at best automated settings was statistically comparable to previously established clinical settings. The optimization algorithm converged after testing 15.1±0.7 settings when maximum safe exploration boundaries were predefined, and 17.7±4.9 when the algorithm itself determined safe exploration boundaries. SIGNIFICANCE We demonstrate that fully automated DBS programming framework for treatment of tremor is efficient and safe while providing outcomes comparable to that achieved by expert clinicians.
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Affiliation(s)
- Parisa Sarikhani
- Emory University, 101 Woodruff Cir, Suite 4137, Atlanta, Georgia, 30322-1007, UNITED STATES
| | - Benjamin Ferleger
- University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, Pennsylvania, 19104-6243, UNITED STATES
| | - Kyle Mitchell
- Neurology, Duke University, 932 Morreene Rd, Durham, North Carolina, 2770, UNITED STATES
| | - Jill Ostrem
- Neurology, University of California, San Francisco, 1651 Fourth St., Suite 232, San Francisco, California, 94158, UNITED STATES
| | - Jeffrey Herron
- Electrical Engineering, University of Washington, 185 Stevens Way, Room AE100R, Campus Box 352500, Seattle, Washington, 98195, UNITED STATES
| | - Babak Mahmoudi
- Biomedical Informatics, Emory University, 101 Woodruff Cir, Atlanta, Georgia, 30322, UNITED STATES
| | - Svjetlana Miocinovic
- Neurology, Emory University, 12 Executive Park Drive Northeast, Atlanta, Georgia, 30329, UNITED STATES
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9
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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.
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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
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10
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Mishra A, Ramdhani RA. Directional Deep Brain Stimulation in the Treatment of Parkinson's Disease. Neurology 2022. [DOI: 10.17925/usn.2022.18.1.64] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Deep brain stimulation (DBS) is a treatment modality that has been shown to improve the clinical outcomes of individuals with movement disorders, including Parkinson's disease. Directional DBS represents an advance in the field that allows clinicians to better modulate the electrical stimulation to increase therapeutic gains while minimizing side effects. In this review, we summarize the principles of directional DBS, including available technologies and stimulation paradigms, and examine the growing clinical study data with respect to its use in Parkinson's disease.
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11
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Roediger J, Dembek TA, Wenzel G, Butenko K, Kühn AA, Horn A. StimFit-A Data-Driven Algorithm for Automated Deep Brain Stimulation Programming. Mov Disord 2021; 37:574-584. [PMID: 34837245 DOI: 10.1002/mds.28878] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/07/2021] [Accepted: 11/04/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Finding the optimal deep brain stimulation (DBS) parameters from a multitude of possible combinations by trial and error is time consuming and requires highly trained medical personnel. OBJECTIVE We developed an automated algorithm to identify optimal stimulation settings in Parkinson's disease (PD) patients treated with subthalamic nucleus (STN) DBS based on imaging-derived metrics. METHODS Electrode locations and monopolar review data of 612 stimulation settings acquired from 31 PD patients were used to train a predictive model for therapeutic and adverse stimulation effects. Model performance was then evaluated within the training cohort using cross-validation and on an independent cohort of 19 patients. We inverted the model by applying a brute-force approach to determine the optimal stimulation sites in the target region. Finally, an optimization algorithm was established to identify optimal stimulation parameters. Suggested stimulation parameters were compared to the ones applied in clinical practice. RESULTS Predicted motor outcome correlated with observed outcome (R = 0.57, P < 10-10 ) across patients within the training cohort. In the test cohort, the model explained 28% of the variance in motor outcome differences between settings. The stimulation site for maximum motor improvement was located at the dorsolateral border of the STN. When compared to two empirical settings, model-based suggestions more closely matched the setting with superior motor improvement. CONCLUSION We developed and validated a data-driven model that can suggest stimulation parameters leading to optimal motor improvement while minimizing the risk of stimulation-induced side effects. This approach might provide guidance for DBS programming in the future. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Jan Roediger
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité University Medicine Berlin, Charitéplatz 1, Berlin, 10117, Germany.,Einstein Center for Neurosciences Berlin, Charité University Medicine Berlin, Charitéplatz 1, Berlin, 10117, Germany
| | - Till A Dembek
- Department of Neurology, Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Gregor Wenzel
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité University Medicine Berlin, Charitéplatz 1, Berlin, 10117, Germany
| | - Konstantin Butenko
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
| | - Andrea A Kühn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité University Medicine Berlin, Charitéplatz 1, Berlin, 10117, Germany.,Berlin School of Mind and Brain, Charité University Medicine, Berlin, Germany.,NeuroCure Clinical Research Centre, Charité University Medicine, Berlin, Germany.,DZNE, German Center for Degenerative Diseases, Berlin, Germany
| | - Andreas Horn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité University Medicine Berlin, Charitéplatz 1, Berlin, 10117, Germany
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