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Ranjan M, Mahoney JJ, Rezai AR. Neurosurgical neuromodulation therapy for psychiatric disorders. Neurotherapeutics 2024; 21:e00366. [PMID: 38688105 PMCID: PMC11070709 DOI: 10.1016/j.neurot.2024.e00366] [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: 10/16/2023] [Revised: 04/09/2024] [Accepted: 04/16/2024] [Indexed: 05/02/2024] Open
Abstract
Psychiatric disorders are among the leading contributors to global disease burden and disability. A significant portion of patients with psychiatric disorders remain treatment-refractory to best available therapy. With insights from the neurocircuitry of psychiatric disorders and extensive experience of neuromodulation with deep brain stimulation (DBS) in movement disorders, DBS is increasingly being considered to modulate the neural network in psychiatric disorders. Currently, obsessive-compulsive disorder (OCD) is the only U.S. FDA (United States Food and Drug Administration) approved DBS indication for psychiatric disorders. Medically refractory depression, addiction, and other psychiatric disorders are being explored for DBS neuromodulation. Studies evaluating DBS for psychiatric disorders are promising but lack larger, controlled studies. This paper presents a brief review and the current state of DBS and other neurosurgical neuromodulation therapies for OCD and other psychiatric disorders. We also present a brief review of MR-guided Focused Ultrasound (MRgFUS), a novel form of neurosurgical neuromodulation, which can target deep subcortical structures similar to DBS, but in a noninvasive fashion. Early experiences of neurosurgical neuromodulation therapies, including MRgFUS neuromodulation are encouraging in psychiatric disorders; however, they remain investigational. Currently, DBS and VNS are the only FDA approved neurosurgical neuromodulation options in properly selected cases of OCD and depression, respectively.
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Affiliation(s)
- Manish Ranjan
- Department of Neurosurgery, WVU Rockefeller Neuroscience Institute, Morgantown, WV, USA.
| | - James J Mahoney
- Department of Behavioral Medicine and Psychiatry, WVU Rockefeller Neuroscience Institute, Morgantown, WV, USA; Department of Neuroscience, WVU Rockefeller Neuroscience Institute, Morgantown, WV, USA
| | - Ali R Rezai
- Department of Neurosurgery, WVU Rockefeller Neuroscience Institute, Morgantown, WV, USA; Department of Neuroscience, WVU Rockefeller Neuroscience Institute, Morgantown, WV, USA
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Widge AS. Closed-Loop Deep Brain Stimulation for Psychiatric Disorders. Harv Rev Psychiatry 2023; 31:162-171. [PMID: 37171475 PMCID: PMC10188203 DOI: 10.1097/hrp.0000000000000367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
ABSTRACT Deep brain stimulation (DBS) is a well-established approach to treating medication-refractory neurological disorders and holds promise for treating psychiatric disorders. Despite strong open-label results in extremely refractory patients, DBS has struggled to meet endpoints in randomized controlled trials. A major challenge is stimulation "dosing"-DBS systems have many adjustable parameters, and clinicians receive little feedback on whether they have chosen the correct parameters for an individual patient. Multiple groups have proposed closed loop technologies as a solution. These systems sense electrical activity, identify markers of an (un)desired state, then automatically deliver or adjust stimulation to alter that electrical state. Closed loop DBS has been successfully deployed in movement disorders and epilepsy. The availability of that technology, as well as advances in opportunities for invasive research with neurosurgical patients, has yielded multiple pilot demonstrations in psychiatric illness. Those demonstrations split into two schools of thought, one rooted in well-established diagnoses and symptom scales, the other in the more experimental Research Domain Criteria (RDoC) framework. Both are promising, and both are limited by the boundaries of current stimulation technology. They are in turn driving advances in implantable recording hardware, signal processing, and stimulation paradigms. The combination of these advances is likely to change both our understanding of psychiatric neurobiology and our treatment toolbox, though the timeframe may be limited by the realities of implantable device development.
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Affiliation(s)
- Alik S Widge
- From the Department of Psychiatry & Behavioral Sciences and Medical Discovery Team on Addictions, University of Minnesota
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Sensor Technology and Intelligent Systems in Anorexia Nervosa: Providing Smarter Healthcare Delivery Systems. BIOMED RESEARCH INTERNATIONAL 2022; 2022:1955056. [PMID: 36193321 PMCID: PMC9526573 DOI: 10.1155/2022/1955056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 09/06/2022] [Indexed: 11/22/2022]
Abstract
Ubiquitous technology, big data, more efficient electronic health records, and predictive analytics are now at the core of smart healthcare systems supported by artificial intelligence. In the present narrative review, we focus on sensing technologies for the healthcare of Anorexia Nervosa (AN). We employed a framework inspired by the Interpersonal Neurobiology Theory (IPNB), which posits that human experience is characterized by a flow of energy and information both within us (within our whole body), and between us (in the connections we have with others and with nature). In line with this framework, we focused on sensors designed to evaluate bodily processes (body sensors such as implantable sensors, epidermal sensors, and wearable and portable sensors), human social interaction (sociometric sensors), and the physical environment (indoor and outdoor ambient sensors). There is a myriad of man-made sensors as well as nature-based sensors such as plants that can be used to design and deploy intelligent systems for human monitoring and healthcare. In conclusion, sensing technologies and intelligent systems can be employed for smarter healthcare of AN and help to relieve the burden of health professionals. However, there are technical, ethical, and environmental sustainability issues that must be considered prior to implementing these systems. A joint collaboration of professionals and other members of the society involved in the healthcare of individuals with AN can help in the development of these systems. The evolution of cyberphysical systems should also be considered in these collaborations.
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Mahoney JJ, Koch-Gallup N, Scarisbrick DM, Berry JH, Rezai AR. Deep brain stimulation for psychiatric disorders and behavioral/cognitive-related indications: Review of the literature and implications for treatment. J Neurol Sci 2022; 437:120253. [DOI: 10.1016/j.jns.2022.120253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 02/23/2022] [Accepted: 04/03/2022] [Indexed: 11/15/2022]
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Elias GJB, Germann J, Boutet A, Loh A, Li B, Pancholi A, Beyn ME, Naheed A, Bennett N, Pinto J, Bhat V, Giacobbe P, Woodside DB, Kennedy SH, Lozano AM. 3 T MRI of rapid brain activity changes driven by subcallosal cingulate deep brain stimulation. Brain 2021; 145:2214-2226. [PMID: 34919630 DOI: 10.1093/brain/awab447] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 11/08/2021] [Accepted: 11/18/2021] [Indexed: 11/14/2022] Open
Abstract
Deep brain stimulation targeting the subcallosal cingulate area (SCC-DBS), a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While SCC-DBS drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0 Tesla functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of twelve patients with fully implanted SCC-DBS devices. Four additional SCC-DBS patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n=78 acquisitions overall) during i) inactive DBS; ii) clinically optimal active DBS; iii) suboptimal active DBS. All scans were acquired within a single MRI session, each separated by a 5-minute washout period. Analysis of the amplitude of low frequency fluctuations (ALFF) in each sequence indicated that clinically optimal SCC-DBS reduced spontaneous brain activity in several areas, including bilateral dorsal anterior cingulate cortex (dACC), posterior cingulate cortex (PCC), precuneus, and left inferior parietal lobule (pBonferroni<0.0001). Stimulation-induced dACC signal reduction correlated with immediate within-session mood fluctuations, was greater at optimal versus suboptimal settings, and related to local cingulum bundle engagement. Moreover, linear modelling showed that immediate changes in dACC, PCC, and precuneus activity could predict individual long-term antidepressant improvement. A model derived from the primary cohort that incorporated ALFF changes in these three areas (along with pre-operative symptom severity) explained 55% of the variance in clinical improvement in that cohort. The same model also explained 93% of the variance in the out-of-sample validation cohort. Additionally all three brain areas exhibited significant changes in functional connectivity between active and inactive DBS states (pBonferroni<0.01). These results provide insight into the network-level mechanisms of SCC-DBS and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.
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Affiliation(s)
- Gavin J B Elias
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada.,Krembil Research Institute, University of Toronto, Toronto, Canada
| | - Jürgen Germann
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada.,Krembil Research Institute, University of Toronto, Toronto, Canada
| | - Alexandre Boutet
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada.,Krembil Research Institute, University of Toronto, Toronto, Canada.,Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Aaron Loh
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada.,Krembil Research Institute, University of Toronto, Toronto, Canada
| | - Bryan Li
- Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Aditya Pancholi
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada
| | - Michelle E Beyn
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada
| | - Asma Naheed
- Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Nicole Bennett
- Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Jessica Pinto
- Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Venkat Bhat
- Department of Psychiatry, University Health Network and University of Toronto, Toronto, Canada
| | - Peter Giacobbe
- Department of Psychiatry, Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
| | - D Blake Woodside
- Department of Psychiatry, University Health Network and University of Toronto, Toronto, Canada
| | - Sidney H Kennedy
- Krembil Research Institute, University of Toronto, Toronto, Canada.,Department of Psychiatry, University Health Network and University of Toronto, Toronto, Canada
| | - Andres M Lozano
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Canada.,Krembil Research Institute, University of Toronto, Toronto, Canada
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