1
|
Al-Sharif NB, Zavaliangos-Petropulu A, Narr KL. A review of diffusion MRI in mood disorders: mechanisms and predictors of treatment response. Neuropsychopharmacology 2024; 50:211-229. [PMID: 38902355 PMCID: PMC11525636 DOI: 10.1038/s41386-024-01894-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 05/15/2024] [Accepted: 05/21/2024] [Indexed: 06/22/2024]
Abstract
By measuring the molecular diffusion of water molecules in brain tissue, diffusion MRI (dMRI) provides unique insight into the microstructure and structural connections of the brain in living subjects. Since its inception, the application of dMRI in clinical research has expanded our understanding of the possible biological bases of psychiatric disorders and successful responses to different therapeutic interventions. Here, we review the past decade of diffusion imaging-based investigations with a specific focus on studies examining the mechanisms and predictors of therapeutic response in people with mood disorders. We present a brief overview of the general application of dMRI and key methodological developments in the field that afford increasingly detailed information concerning the macro- and micro-structural properties and connectivity patterns of white matter (WM) pathways and their perturbation over time in patients followed prospectively while undergoing treatment. This is followed by a more in-depth summary of particular studies using dMRI approaches to examine mechanisms and predictors of clinical outcomes in patients with unipolar or bipolar depression receiving pharmacological, neurostimulation, or behavioral treatments. Limitations associated with dMRI research in general and with treatment studies in mood disorders specifically are discussed, as are directions for future research. Despite limitations and the associated discrepancies in findings across individual studies, evolving research strongly indicates that the field is on the precipice of identifying and validating dMRI biomarkers that could lead to more successful personalized treatment approaches and could serve as targets for evaluating the neural effects of novel treatments.
Collapse
Affiliation(s)
- Noor B Al-Sharif
- Departments of Neurology and Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
| | - Artemis Zavaliangos-Petropulu
- Departments of Neurology and Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Katherine L Narr
- Departments of Neurology and Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| |
Collapse
|
2
|
Li D, Zhang Y, Lai L, Hao J, Wang X, Zhao Z, Cui X, Xiang J, Wang B. The impact of indirect structure on functional connectivity in schizophrenia using a multiplex brain network. J Psychiatr Res 2024; 179:257-265. [PMID: 39321524 DOI: 10.1016/j.jpsychires.2024.09.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Revised: 08/21/2024] [Accepted: 09/19/2024] [Indexed: 09/27/2024]
Abstract
It is known that abnormal functional connectivity (FC) in schizophrenia (SZ) is closely related to structural connectivity (SC). We speculate that indirect SC also have an impact on FC in SZ patients. Conventional single-layer network has limitations for studying the relationship between indirect SC and FC. Thus, this study constructed a multiplex network based on structural connectivity and functional connectivity (SC-FC). The SC-FC bandwidth and SC-FC cost are used to analyze the impact of indirect SC on FC. Moreover, this paper proposed mediation ability, mediation cost, mediated strength and mediated cost to quantify the effects of mediator nodes and mediated nodes on indirect SC. The results show that SZ patients exhibit lower SC-FC bandwidth and SC-FC cost compared to healthy controls (HC), which could be caused by the limbic and subcortical network (LSN), default mode network (DMN) and visual network (VN). The mediator and mediated nodes in indirect SC of SZ patients also showed diminished effects. These findings suggest that functional communication ability and cost in SZ patients are influenced by indirect SC. This study provides new perspectives for understanding the relationship between indirect SC and FC, and provides strong evidence for interpreting the physiological mechanisms of SZ patients.
Collapse
Affiliation(s)
- Dandan Li
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China.
| | - Yating Zhang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China
| | - Luyao Lai
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China
| | - Jianchao Hao
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China
| | - Xuedong Wang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China
| | - Zhenyu Zhao
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China
| | - Xiaohong Cui
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China
| | - Jie Xiang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China
| | - Bin Wang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, 030024, China
| |
Collapse
|
3
|
Tura A, Promet L, Goya-Maldonado R. Structural-functional connectomics in major depressive disorder following aiTBS treatment. Psychiatry Res 2024; 342:116217. [PMID: 39369459 DOI: 10.1016/j.psychres.2024.116217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 08/16/2024] [Accepted: 09/22/2024] [Indexed: 10/08/2024]
Abstract
Major depressive disorder (MDD) has been associated with changes in the structural (SC) and functional connectivity (FC) of the brain. This study investigated the effects of accelerated intermittent theta burst stimulation (aiTBS) on SC-FC coupling and graph theory measures, focusing on the association between baseline SC-FC coupling of the dorsolateral prefrontal cortex (dlPFC) and clinical improvement. In a randomized, sham-controlled, quadruple-blind, crossover study, aiTBS was delivered to the left dlPFC of depressed patients with MDD, and diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rsfMRI) data were acquired. In 77 MDD patients, significantly increased whole-brain SC-FC coupling was observed, primarily driven by default mode network (DMN) SC-FC coupling, along with increased somatomotor network FC, and decreased FC between the DMN hubs and limbic regions after active aiTBS. Furthermore, significant increases were observed in structural global and local efficiency measures that were not specific to the stimulation condition (active/sham aiTBS). However, these changes did not significantly correlate with clinical improvement. Notably, baseline SC-FC coupling of the left dlPFC was a significant predictor of clinical improvement. Our findings highlight the potential of left dlPFC SC-FC coupling as a predictor of aiTBS treatment outcomes, as well as the effect of aiTBS in enhancing SC-FC coupling.
Collapse
Affiliation(s)
- Asude Tura
- Laboratory of Systems Neuroscience and Imaging in Psychiatry (SNIP-Lab), Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), University of Göttingen, Göttingen, Germany
| | - Liisi Promet
- Laboratory of Systems Neuroscience and Imaging in Psychiatry (SNIP-Lab), Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), University of Göttingen, Göttingen, Germany
| | - Roberto Goya-Maldonado
- Laboratory of Systems Neuroscience and Imaging in Psychiatry (SNIP-Lab), Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), University of Göttingen, Göttingen, Germany.
| |
Collapse
|
4
|
Briley PM, Webster L, Boutry C, Oh H, Auer DP, Liddle PF, Morriss R. Magnetic resonance imaging connectivity features associated with response to transcranial magnetic stimulation in major depressive disorder. Psychiatry Res Neuroimaging 2024; 342:111846. [PMID: 38908353 DOI: 10.1016/j.pscychresns.2024.111846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 03/23/2024] [Accepted: 06/11/2024] [Indexed: 06/24/2024]
Abstract
Transcranial magnetic stimulation (TMS) is an FDA-approved neuromodulation treatment for major depressive disorder (MDD), thought to work by altering dysfunctional brain connectivity pathways, or by indirectly modulating the activity of subcortical brain regions. Clinical response to TMS remains highly variable, highlighting the need for baseline predictors of response and for understanding brain changes associated with response. This systematic review examined brain connectivity features, and changes in connectivity features, associated with clinical improvement following TMS in MDD. Forty-one studies met inclusion criteria, including 1097 people with MDD. Most studies delivered one of two types of TMS to left dorsolateral prefrontal cortex and measured connectivity using resting-state functional MRI. The subgenual anterior cingulate cortex was the most well-studied brain region, particularly its connectivity with the TMS target or with the "executive control network" of brain regions. There was marked heterogeneity in findings. There is a need for greater understanding of how cortical TMS modulates connectivity with, and the activity of, subcortical regions, and how these effects change within and across treatment sessions.
Collapse
Affiliation(s)
- P M Briley
- Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom; Nottingham National Institute for Health and Care Research (NIHR) Biomedical Research Centre, Nottingham, United Kingdom; Institute of Mental Health, Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, United Kingdom.
| | - L Webster
- Nottingham National Institute for Health and Care Research (NIHR) Biomedical Research Centre, Nottingham, United Kingdom; Institute of Mental Health, Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, United Kingdom
| | - C Boutry
- Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom; Institute of Mental Health, Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, United Kingdom; NIHR Applied Research Collaboration East Midlands, University of Nottingham, Nottingham, United Kingdom
| | - H Oh
- Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom; Nottingham National Institute for Health and Care Research (NIHR) Biomedical Research Centre, Nottingham, United Kingdom; Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
| | - D P Auer
- Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom; Nottingham National Institute for Health and Care Research (NIHR) Biomedical Research Centre, Nottingham, United Kingdom; Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
| | - P F Liddle
- Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom; Institute of Mental Health, Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, United Kingdom
| | - R Morriss
- Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom; Nottingham National Institute for Health and Care Research (NIHR) Biomedical Research Centre, Nottingham, United Kingdom; Institute of Mental Health, Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, United Kingdom; NIHR Applied Research Collaboration East Midlands, University of Nottingham, Nottingham, United Kingdom; NIHR Mental Health (MindTech) Health Technology Collaboration, University of Nottingham, Nottingham, United Kingdom
| |
Collapse
|
5
|
Park TY, Franke L, Pieper S, Haehn D, Ning L. A review of algorithms and software for real-time electric field modeling techniques for transcranial magnetic stimulation. Biomed Eng Lett 2024; 14:393-405. [PMID: 38645587 PMCID: PMC11026361 DOI: 10.1007/s13534-024-00373-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 02/27/2024] [Accepted: 03/04/2024] [Indexed: 04/23/2024] Open
Abstract
Transcranial magnetic stimulation (TMS) is a device-based neuromodulation technique increasingly used to treat brain diseases. Electric field (E-field) modeling is an important technique in several TMS clinical applications, including the precision stimulation of brain targets with accurate stimulation density for the treatment of mental disorders and the localization of brain function areas for neurosurgical planning. Classical methods for E-field modeling usually take a long computation time. Fast algorithms are usually developed with significantly lower spatial resolutions that reduce the prediction accuracy and limit their usage in real-time or near real-time TMS applications. This review paper discusses several modern algorithms for real-time or near real-time TMS E-field modeling and their advantages and limitations. The reviewed methods include techniques such as basis representation techniques and deep neural-network-based methods. This paper also provides a review of software tools that can integrate E-field modeling with navigated TMS, including a recent software for real-time navigated E-field mapping based on deep neural-network models.
Collapse
Affiliation(s)
- Tae Young Park
- Bionics Research Center, Biomedical Research Division, Korea Institute of Science and Technology, Seoul, 02792 Republic of Korea
- Division of Biomedical Science and Technology, KIST School, Korea University of Science and Technology, Seoul, 02792 Republic of Korea
- Brigham and Women’s Hospital, Boston, MA 02115 USA
| | - Loraine Franke
- University of Massachusetts Boston, Boston, MA 02125 USA
| | | | - Daniel Haehn
- University of Massachusetts Boston, Boston, MA 02125 USA
| | - Lipeng Ning
- Brigham and Women’s Hospital, Boston, MA 02115 USA
- Harvard Medical School, Boston, MA 02115 USA
| |
Collapse
|
6
|
Dong MS, Rokicki J, Dwyer D, Papiol S, Streit F, Rietschel M, Wobrock T, Müller-Myhsok B, Falkai P, Westlye LT, Andreassen OA, Palaniyappan L, Schneider-Axmann T, Hasan A, Schwarz E, Koutsouleris N. Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis. Transl Psychiatry 2024; 14:196. [PMID: 38664377 PMCID: PMC11045783 DOI: 10.1038/s41398-024-02903-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 04/03/2024] [Accepted: 04/08/2024] [Indexed: 04/28/2024] Open
Abstract
The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.
Collapse
Grants
- FA-210/1 Deutsche Forschungsgemeinschaft (German Research Foundation)
- SCHW 1768/1-1 Deutsche Forschungsgemeinschaft (German Research Foundation)
- FA-210/1 Deutsche Forschungsgemeinschaft (German Research Foundation)
- SCHW 1768/1-1 Deutsche Forschungsgemeinschaft (German Research Foundation)
- FA-210/1 Deutsche Forschungsgemeinschaft (German Research Foundation)
- SCHW 1768/1-1 Deutsche Forschungsgemeinschaft (German Research Foundation)
- FA-210/1 Deutsche Forschungsgemeinschaft (German Research Foundation)
- 01ZX1904A Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie (Federal Ministry for Education, Science, Research and Technology)
- 01KU1905A Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie (Federal Ministry for Education, Science, Research and Technology)
- 01ZX1904A Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie (Federal Ministry for Education, Science, Research and Technology)
- 01KU1905A Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie (Federal Ministry for Education, Science, Research and Technology)
- 01ZX1904A Bundesministerium für Bildung, Wissenschaft und Kultur (Federal Ministry of Education, Science and Culture)
- ENP-161423 Gouvernement du Canada | Canadian Institutes of Health Research (Instituts de Recherche en Santé du Canada)
Collapse
Affiliation(s)
- Mark Sen Dong
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian-University of Munich, Munich, Germany
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Jaroslav Rokicki
- Centre of Research and Education in Forensic Psychiatry, Oslo Univerisity Hospital, Oslo, Norway
| | - Dominic Dwyer
- The University of Melbourne, Melbourne, VIC, Australia
| | - Sergi Papiol
- Max Planck Institute of Psychiatry, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Fabian Streit
- Department for Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Hector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marcella Rietschel
- Department for Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Thomas Wobrock
- Centre for Mental Health, Darmstadt-Dieburg District Clinic, Gross-Umstadt, Germany
| | | | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian-University of Munich, Munich, Germany
- Max Planck Institute of Psychiatry, Munich, Germany
- Partner site Munich-Augsburg, DZPG (German Centre for Mental Health), Munich / Augsburg, Germany
| | | | - Ole A Andreassen
- Centre for Precision Psychiatry, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada
- Robarts Research Institute, Western University, London Ontario, Canada
| | - Thomas Schneider-Axmann
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian-University of Munich, Munich, Germany
| | - Alkomiet Hasan
- Partner site Munich-Augsburg, DZPG (German Centre for Mental Health), Munich / Augsburg, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Emanuel Schwarz
- Department for Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Hector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilian-University of Munich, Munich, Germany.
- Max Planck Institute of Psychiatry, Munich, Germany.
- Partner site Munich-Augsburg, DZPG (German Centre for Mental Health), Munich / Augsburg, Germany.
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| |
Collapse
|
7
|
Razza LB, Wischnewski M, Suen P, De Smet S, da Silva PHR, Catoira B, Brunoni AR, Vanderhasselt MA. An electric field modeling study with meta-analysis to understand the antidepressant effects of transcranial direct current stimulation (tDCS). REVISTA BRASILEIRA DE PSIQUIATRIA (SAO PAULO, BRAZIL : 1999) 2023; 45:518-529. [PMID: 37400373 PMCID: PMC10897770 DOI: 10.47626/1516-4446-2023-3116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 06/08/2023] [Indexed: 07/05/2023]
Abstract
OBJECTIVE Transcranial direct current stimulation (tDCS) has mixed effects for major depressive disorder (MDD) symptoms, partially owing to large inter-experimental variability in tDCS protocols and their correlated induced electric fields (E-fields). We investigated whether the E-field strength of distinct tDCS parameters was associated with antidepressant effect. METHODS A meta-analysis was performed with placebo-controlled clinical trials of tDCS enrolling MDD patients. PubMed, EMBASE, and Web of Science were searched from inception to March 10, 2023. Effect sizes of tDCS protocols were correlated with E-field simulations (SimNIBS) of brain regions of interest (bilateral dorsolateral prefrontal cortex [DLPFC] and bilateral subgenual anterior cingulate cortex [sgACC]). Moderators of tDCS responses were also investigated. RESULTS A total of 20 studies were included (21 datasets, 1,008 patients), using 11 distinct tDCS protocols. Results revealed a moderate effect for MDD (g = 0.41, 95%CI 0.18-0.64), while cathode position and treatment strategy were found to be moderators of response. A negative association between effect size and tDCS-induced E-field magnitude was seen, with stronger E-fields in the right frontal and medial parts of the DLPFC (targeted by the cathode) leading to smaller effects. No association was found for the left DLPFC and the bilateral sgACC. An optimized tDCS protocol is proposed. CONCLUSION Our results highlight the need for a standardized tDCS protocol in MDD clinical trials.
Collapse
Affiliation(s)
- Lais B Razza
- Department of Head and Skin, Psychiatry and Medical Psychology, Ghent University Hospital, Ghent University, Ghent, Belgium. Ghent Experimental Psychiatry Lab, Ghent, Belgium
| | - Miles Wischnewski
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Paulo Suen
- Serviço Interdisciplinar de Neuromodulação, Laboratório de Neurociências, Instituto de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Stefanie De Smet
- Department of Head and Skin, Psychiatry and Medical Psychology, Ghent University Hospital, Ghent University, Ghent, Belgium. Ghent Experimental Psychiatry Lab, Ghent, Belgium
| | - Pedro Henrique Rodrigues da Silva
- Serviço Interdisciplinar de Neuromodulação, Laboratório de Neurociências, Instituto de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Beatriz Catoira
- Department of Head and Skin, Psychiatry and Medical Psychology, Ghent University Hospital, Ghent University, Ghent, Belgium. Ghent Experimental Psychiatry Lab, Ghent, Belgium. Department of Psychiatry, Free University Brussels, Ixelles, Belgium
| | - André R Brunoni
- Serviço Interdisciplinar de Neuromodulação, Laboratório de Neurociências, Instituto de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, SP, Brazil. Departamento de Clínica Médica, Hospital das Clínicas, Faculdade de Medicina, USP, São Paulo, SP, Brazil. Hospital das Clínicas, USP, São Paulo, SP, Brazil
| | - Marie-Anne Vanderhasselt
- Department of Head and Skin, Psychiatry and Medical Psychology, Ghent University Hospital, Ghent University, Ghent, Belgium. Ghent Experimental Psychiatry Lab, Ghent, Belgium
| |
Collapse
|
8
|
Quinn DK, Upston J, Jones TR, Gibson BC, Olmstead TA, Yang J, Price AM, Bowers-Wu DH, Durham E, Hazlewood S, Farrar DC, Miller J, Lloyd MO, Garcia CA, Ojeda CJ, Hager BW, Vakhtin AA, Abbott CC. Electric field distribution predicts efficacy of accelerated intermittent theta burst stimulation for late-life depression. Front Psychiatry 2023; 14:1215093. [PMID: 37593449 PMCID: PMC10427506 DOI: 10.3389/fpsyt.2023.1215093] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 07/13/2023] [Indexed: 08/19/2023] Open
Abstract
Introduction Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention for late-life depression (LLD) but may have lower rates of response and remission owing to age-related brain changes. In particular, rTMS induced electric field strength may be attenuated by cortical atrophy in the prefrontal cortex. To identify clinical characteristics and treatment parameters associated with response, we undertook a pilot study of accelerated fMRI-guided intermittent theta burst stimulation (iTBS) to the right dorsolateral prefrontal cortex in 25 adults aged 50 or greater diagnosed with LLD and qualifying to receive clinical rTMS. Methods Participants underwent baseline behavioral assessment, cognitive testing, and structural and functional MRI to generate individualized targets and perform electric field modeling. Forty-five sessions of iTBS were delivered over 9 days (1800 pulses per session, 50-min inter-session interval). Assessments and testing were repeated after 15 sessions (Visit 2) and 45 sessions (Visit 3). Primary outcome measure was the change in depressive symptoms on the Inventory of Depressive Symptomatology-30-Clinician (IDS-C-30) from Visit 1 to Visit 3. Results Overall there was a significant improvement in IDS score with the treatment (Visit 1: 38.6; Visit 2: 31.0; Visit 3: 21.3; mean improvement 45.5%) with 13/25 (52%) achieving response and 5/25 (20%) achieving remission (IDS-C-30 < 12). Electric field strength and antidepressant effect were positively correlated in a subregion of the ventrolateral prefrontal cortex (VLPFC) (Brodmann area 47) and negatively correlated in the posterior dorsolateral prefrontal cortex (DLPFC). Conclusion Response and remission rates were lower than in recently published trials of accelerated fMRI-guided iTBS to the left DLPFC. These results suggest that sufficient electric field strength in VLPFC may be a contributor to effective rTMS, and that modeling to optimize electric field strength in this area may improve response and remission rates. Further studies are needed to clarify the relationship of induced electric field strength with antidepressant effects of rTMS for LLD.
Collapse
Affiliation(s)
- Davin K. Quinn
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Joel Upston
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Thomas R. Jones
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Benjamin C. Gibson
- Department of Psychology, University of New Mexico, Albuquerque, NM, United States
| | - Tessa A. Olmstead
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Justine Yang
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | | | - Dorothy H. Bowers-Wu
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Erick Durham
- Department of Psychiatry, Texas Tech University, El Paso, TX, United States
| | - Shawn Hazlewood
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Danielle C. Farrar
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Jeremy Miller
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Megan O. Lloyd
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Crystal A. Garcia
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Cesar J. Ojeda
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | - Brant W. Hager
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| | | | - Christopher C. Abbott
- Department of Psychiatry and Behavioral Sciences, UNM, Albuquerque, NM, United States
| |
Collapse
|
9
|
Tura A, Goya-Maldonado R. Brain connectivity in major depressive disorder: a precision component of treatment modalities? Transl Psychiatry 2023; 13:196. [PMID: 37296121 DOI: 10.1038/s41398-023-02499-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 05/15/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023] Open
Abstract
Major depressive disorder (MDD) is a very prevalent mental disorder that imposes an enormous burden on individuals, society, and health care systems. Most patients benefit from commonly used treatment methods such as pharmacotherapy, psychotherapy, electroconvulsive therapy (ECT), and repetitive transcranial magnetic stimulation (rTMS). However, the clinical decision on which treatment method to use remains generally informed and the individual clinical response is difficult to predict. Most likely, a combination of neural variability and heterogeneity in MDD still impedes a full understanding of the disorder, as well as influences treatment success in many cases. With the help of neuroimaging methods like functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), the brain can be understood as a modular set of functional and structural networks. In recent years, many studies have investigated baseline connectivity biomarkers of treatment response and the connectivity changes after successful treatment. Here, we systematically review the literature and summarize findings from longitudinal interventional studies investigating the functional and structural connectivity in MDD. By compiling and discussing these findings, we recommend the scientific and clinical community to deepen the systematization of findings to pave the way for future systems neuroscience roadmaps that include brain connectivity parameters as a possible precision component of the clinical evaluation and therapeutic decision.
Collapse
Affiliation(s)
- Asude Tura
- Laboratory of Systems Neuroscience and Imaging in Psychiatry (SNIP-Lab), Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Göttingen, Germany
| | - Roberto Goya-Maldonado
- Laboratory of Systems Neuroscience and Imaging in Psychiatry (SNIP-Lab), Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Göttingen, Germany.
| |
Collapse
|
10
|
Chen C, Li B, Zhang S, Liu Z, Wang Y, Xu M, Ji Y, Wang S, Sun G, Liu K. Aberrant structural and functional alterations in postpartum depression: a combined voxel-based morphometry and resting-state functional connectivity study. Front Neurosci 2023; 17:1138561. [PMID: 37304034 PMCID: PMC10249609 DOI: 10.3389/fnins.2023.1138561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 04/28/2023] [Indexed: 06/13/2023] Open
Abstract
Objectives Postpartum depression (PPD) is a severe postpartum psychiatric disorder with unclear pathogenesis. Previous neuroimaging studies have reported structural or functional alterations in areas associated with emotion regulation, cognitive disorder, and parenting behaviors of PPD. The primary goal of this investigation was to explore the presence of brain structural alterations and relevant functional changes in PPD patients. Methods A total of 28 patients and 30 matched healthy postnatal women (HPW) underwent both three-dimensional T1-weighted magnetic resonance imaging (MRI) and resting-state functional MRI. Structural analysis was performed by voxel-based morphometry (VBM), followed by resting-state functional analysis using a seed-based whole-brain functional connectivity (FC) approach with abnormal gray matter volume (GMV) regions as seed. Results Compared with HPW, the PPD patients showed increased GMV in the left dorsolateral prefrontal cortex (DLPFC.L), the right precentral gyrus (PrCG.R), and the orbitofrontal cortex (OFC). In the PPD group, the DLPFC.L showed increased FC with the right anterior cingulate and paracingulate gyri (ACG.R) and the right middle frontal gyrus (MFG.R); the FC between the PrCG.R and the right median cingulate and paracingulate gyri (DCG.R) exhibited enhanced; the OFC showed increased FC with MFG.R and the left inferior occipital gyrus (IOG.L). In PPD, GMV of DLPFC.L was positively correlated with EDPS scores (r = 0.409 p = 0.031), and FC of PrCG.R-DCG.R was positively correlated with EDPS scores (r = 0.483 p = 0.020). Conclusion Structural and functional damage of the DLPFC.L and OFC is associated with cognitive disorders and parenting behaviors in PPD, while structural abnormalities of the DLPFC.L and PrCG.R are involved in impaired executive function. The increased GMV of DLPFC.L may be a unique structural pathological mechanism of PPD related to the inability of PPD patients to withstand long-term parenting stress. These findings have important implications for understanding neural mechanisms in PPD.
Collapse
Affiliation(s)
| | - Bo Li
- Department of Radiology, The 960th Hospital of the PLA Joint Logistic Support Force, Jinan, Shandong, China
| | - Shufen Zhang
- Department of Obstetrics, Shandong Second Provincial General Hospital, Jinan, China
| | - Zhe Liu
- Department of Radiology, The 960th Hospital of the PLA Joint Logistic Support Force, Jinan, Shandong, China
| | - Yu Wang
- Department of Radiology, The 960th Hospital of the PLA Joint Logistic Support Force, Jinan, Shandong, China
| | - Minghe Xu
- Department of Radiology, The 960th Hospital of the PLA Joint Logistic Support Force, Jinan, Shandong, China
| | - Yuqing Ji
- Department of Radiology, The 960th Hospital of the PLA Joint Logistic Support Force, Jinan, Shandong, China
| | - Shuang Wang
- Department of Radiology, The 960th Hospital of the PLA Joint Logistic Support Force, Jinan, Shandong, China
| | - Gang Sun
- Department of Radiology, The 960th Hospital of the PLA Joint Logistic Support Force, Jinan, Shandong, China
| | - Kai Liu
- Department of Radiology, The 960th Hospital of the PLA Joint Logistic Support Force, Jinan, Shandong, China
| |
Collapse
|
11
|
Wu GR, Baeken C. The left ventrolateral prefrontal cortex as a more optimal target for accelerated rTMS treatment protocols for depression? Brain Stimul 2023; 16:642-644. [PMID: 36935001 DOI: 10.1016/j.brs.2023.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 03/14/2023] [Indexed: 03/19/2023] Open
Affiliation(s)
- Guo-Rong Wu
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing, China; School of Psychology, Jiangxi Normal University, Nanchang, China; Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, Ghent, Belgium.
| | - Chris Baeken
- Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, Ghent, Belgium; Vrije Universiteit Brussel (VUB), Department of Psychiatry, University Hospital (UZBrussel), Brussels, Belgium; Eindhoven University of Technology, Department of Electrical Engineering, Eindhoven, the Netherlands.
| |
Collapse
|
12
|
Caulfield KA, Fleischmann HH, George MS, McTeague LM. A transdiagnostic review of safety, efficacy, and parameter space in accelerated transcranial magnetic stimulation. J Psychiatr Res 2022; 152:384-396. [PMID: 35816982 PMCID: PMC10029148 DOI: 10.1016/j.jpsychires.2022.06.038] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/20/2022] [Accepted: 06/24/2022] [Indexed: 01/20/2023]
Abstract
BACKGROUND Accelerated transcranial magnetic stimulation (aTMS) is an emerging delivery schedule of repetitive TMS (rTMS). TMS is "accelerated" by applying two or more stimulation sessions within a day. This three-part review comprehensively reports the safety/tolerability, efficacy, and stimulation parameters affecting response across disorders. METHODS We used the PubMed database to identify studies administering aTMS, which we defined as applying at least two rTMS sessions within one day. RESULTS Our targeted literature search identified 85 aTMS studies across 18 diagnostic and healthy control groups published from July 2001 to June 2022. Excluding overlapping populations, 63 studies delivered 43,873 aTMS sessions using low frequency, high frequency, and theta burst stimulation in 1543 participants. Regarding safety, aTMS studies had similar seizure and side effect incidence rates to those reported for once daily rTMS. One seizure was reported from aTMS (0.0023% of aTMS sessions, compared with 0.0075% in once daily rTMS). The most common side effects were acute headache (28.4%), fatigue (8.6%), and scalp discomfort (8.3%), with all others under 5%. We evaluated aTMS efficacy in 23 depression studies (the condition with the most studies), finding an average response rate of 42.4% and remission rate of 28.4% (range = 0-90.5% for both). Regarding parameters, aTMS studies ranged from 2 to 10 sessions per day over 2-30 treatment days, 10-640 min between sessions, and a total of 9-104 total accelerated TMS sessions per participant (including tapering sessions). Qualitatively, response rate tends to be higher with an increasing number of sessions per day, total sessions, and total pulses. DISCUSSION The literature to date suggests that aTMS is safe and well-tolerated across conditions. Taken together, these early studies suggest potential effectiveness even in highly treatment refractory conditions with the added potential to reduce patient burden while also expediting response time. Future studies are warranted to systematically investigate how key aTMS parameters affect treatment outcome and durability.
Collapse
Affiliation(s)
- Kevin A Caulfield
- Brain Stimulation Division, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA.
| | - Holly H Fleischmann
- Brain Stimulation Division, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA; Department of Psychology, University of Georgia, Athens, GA, USA
| | - Mark S George
- Brain Stimulation Division, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA; Ralph H. Johnson VA Medical Center, Charleston, SC, USA
| | - Lisa M McTeague
- Brain Stimulation Division, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA; Ralph H. Johnson VA Medical Center, Charleston, SC, USA
| |
Collapse
|
13
|
Klooster DCW, Ferguson MA, Boon PAJM, Baeken C. Personalizing Repetitive Transcranial Magnetic Stimulation Parameters for Depression Treatment Using Multimodal Neuroimaging. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:536-545. [PMID: 34800726 DOI: 10.1016/j.bpsc.2021.11.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 10/24/2021] [Accepted: 11/09/2021] [Indexed: 06/13/2023]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a tool that can be used to administer treatment for neuropsychiatric disorders such as major depressive disorder, although the clinical efficacy is still rather modest. Overly general stimulation protocols that consider neither patient-specific depression symptomology nor individualized brain characteristics, such as anatomy or structural and functional connections, may be the cause of the high inter- and intraindividual variability in rTMS clinical responses. Multimodal neuroimaging can provide the necessary insights into individual brain characteristics and can therefore be used to personalize rTMS parameters. Optimal coil positioning should include a three-step process: 1) identify the optimal (indirect) target area based on the exact symptom pattern of the patient; 2) derive the cortical (direct) target location based on functional and/or structural connectomes derived from functional and diffusion magnetic resonance imaging data; and 3) determine the ideal coil position by computational modeling, such that the electric field distribution overlaps with the cortical target. These TMS-induced electric field simulations, derived from anatomical and diffusion magnetic resonance imaging data, can be further applied to compute optimal stimulation intensities. In addition to magnetic resonance imaging, electroencephalography can provide complementary information regarding the ongoing brain oscillations. This information can be used to determine the optimal timing and frequency of the stimuli. The heightened benefits of these personalized stimulation approaches are logically reasoned, but speculative. Randomized clinical trials will be required to compare clinical responses from standard rTMS protocols to personalized protocols. Ultimately, an optimized clinical response may result from precision protocols derived from combinations of personalized stimulation parameters.
Collapse
Affiliation(s)
- Deborah C W Klooster
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium; Ghent Experimental Psychiatry Laboratory, Department of Head and Skin, Ghent University, Ghent, Belgium.
| | - Michael A Ferguson
- Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Paul A J M Boon
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium; Department of Neurology, Ghent University Hospital, Ghent, Belgium
| | - Chris Baeken
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Ghent Experimental Psychiatry Laboratory, Department of Head and Skin, Ghent University, Ghent, Belgium; Department of Psychiatry, University Hospital Brussels, Jette, Belgium
| |
Collapse
|
14
|
Ayyash S, Davis AD, Alders GL, MacQueen G, Strother SC, Hassel S, Zamyadi M, Arnott SR, Harris JK, Lam RW, Milev R, Müller DJ, Kennedy SH, Rotzinger S, Frey BN, Minuzzi L, Hall GB. Exploring brain connectivity changes in major depressive disorder using functional-structural data fusion: A CAN-BIND-1 study. Hum Brain Mapp 2021; 42:4940-4957. [PMID: 34296501 PMCID: PMC8449113 DOI: 10.1002/hbm.25590] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/14/2021] [Accepted: 07/01/2021] [Indexed: 01/23/2023] Open
Abstract
There is a growing interest in examining the wealth of data generated by fusing functional and structural imaging information sources. These approaches may have clinical utility in identifying disruptions in the brain networks that underlie major depressive disorder (MDD). We combined an existing software toolbox with a mathematically dense statistical method to produce a novel processing pipeline for the fast and easy implementation of data fusion analysis (FATCAT‐awFC). The novel FATCAT‐awFC pipeline was then utilized to identify connectivity (conventional functional, conventional structural and anatomically weighted functional connectivy) changes in MDD patients compared to healthy comparison participants (HC). Data were acquired from the Canadian Biomarker Integration Network for Depression (CAN‐BIND‐1) study. Large‐scale resting‐state networks were assessed. We found statistically significant anatomically‐weighted functional connectivity (awFC) group differences in the default mode network and the ventral attention network, with a modest effect size (d < 0.4). Functional and structural connectivity seemed to overlap in significance between one region‐pair within the default mode network. By combining structural and functional data, awFC served to heighten or reduce the magnitude of connectivity differences in various regions distinguishing MDD from HC. This method can help us more fully understand the interconnected nature of structural and functional connectivity as it relates to depression.
Collapse
Affiliation(s)
- Sondos Ayyash
- School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.,Department of Psychology Neuroscience & Behaviour, McMaster University, Hamilton, Ontario, Canada
| | - Andrew D Davis
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | - Gésine L Alders
- Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada
| | - Glenda MacQueen
- Mathison Centre for Mental Health Research and Education, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Ontario, Canada
| | - Stefanie Hassel
- Mathison Centre for Mental Health Research and Education, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada
| | | | - Jacqueline K Harris
- Department of Computer Science, University of Alberta, Edmonton, Alberta, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Roumen Milev
- Departments of Psychiatry and Psychology, Queen's University, Providence Care Hospital, Kingston, Ontario, Canada
| | - Daniel J Müller
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Sidney H Kennedy
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Centre for Mental Health, University Health Network, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Susan Rotzinger
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Centre for Depression and Suicide Studies, and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada.,Mood Disorders Treatment and Research Centre and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, Ontario, Canada
| | - Luciano Minuzzi
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada.,Mood Disorders Treatment and Research Centre and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, Ontario, Canada
| | - Geoffrey B Hall
- School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.,Department of Psychology Neuroscience & Behaviour, McMaster University, Hamilton, Ontario, Canada.,Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada
| | | |
Collapse
|
15
|
Oberman LM, Hynd M, Nielson DM, Towbin KE, Lisanby SH, Stringaris A. Repetitive Transcranial Magnetic Stimulation for Adolescent Major Depressive Disorder: A Focus on Neurodevelopment. Front Psychiatry 2021; 12:642847. [PMID: 33927653 PMCID: PMC8076574 DOI: 10.3389/fpsyt.2021.642847] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 03/18/2021] [Indexed: 12/31/2022] Open
Abstract
Adolescent depression is a potentially lethal condition and a leading cause of disability for this age group. There is an urgent need for novel efficacious treatments since half of adolescents with depression fail to respond to current therapies and up to 70% of those who respond will relapse within 5 years. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising treatment for major depressive disorder (MDD) in adults who do not respond to pharmacological or behavioral interventions. In contrast, rTMS has not demonstrated the same degree of efficacy in adolescent MDD. We argue that this is due, in part, to conceptual and methodological shortcomings in the existing literature. In our review, we first provide a neurodevelopmentally focused overview of adolescent depression. We then summarize the rTMS literature in adult and adolescent MDD focusing on both the putative mechanisms of action and neurodevelopmental factors that may influence efficacy in adolescents. We then identify limitations in the existing adolescent MDD rTMS literature and propose specific parameters and approaches that may be used to optimize efficacy in this uniquely vulnerable age group. Specifically, we suggest ways in which future studies reduce clinical and neural heterogeneity, optimize neuronavigation by drawing from functional brain imaging, apply current knowledge of rTMS parameters and neurodevelopment, and employ an experimental therapeutics platform to identify neural targets and biomarkers for response. We conclude that rTMS is worthy of further investigation. Furthermore, we suggest that following these recommendations in future studies will offer a more rigorous test of rTMS as an effective treatment for adolescent depression.
Collapse
|
16
|
Padberg F, Bulubas L, Mizutani-Tiebel Y, Burkhardt G, Kranz GS, Koutsouleris N, Kambeitz J, Hasan A, Takahashi S, Keeser D, Goerigk S, Brunoni AR. The intervention, the patient and the illness - Personalizing non-invasive brain stimulation in psychiatry. Exp Neurol 2021; 341:113713. [PMID: 33798562 DOI: 10.1016/j.expneurol.2021.113713] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 03/09/2021] [Accepted: 03/28/2021] [Indexed: 02/08/2023]
Abstract
Current hypotheses on the therapeutic action of non-invasive brain stimulation (NIBS) in psychiatric disorders build on the abundant data from neuroimaging studies. This makes NIBS a very promising tool for developing personalized interventions within a precision medicine framework. NIBS methods fundamentally vary in their neurophysiological properties. They comprise repetitive transcranial magnetic stimulation (rTMS) and its variants (e.g. theta burst stimulation - TBS) as well as different types of transcranial electrical stimulation (tES), with the largest body of evidence for transcranial direct current stimulation (tDCS). In the last two decades, significant conceptual progress has been made in terms of NIBS targets, i.e. from single brain regions to neural circuits and to functional connectivity as well as their states, recently leading to brain state modulating closed-loop approaches. Regarding structural and functional brain anatomy, NIBS meets an individually unique constellation, which varies across normal and pathophysiological states. Thus, individual constitutions and signatures of disorders may be indistinguishable at a given time point, but can theoretically be parsed along course- and treatment-related trajectories. We address precision interventions on three levels: 1) the NIBS intervention, 2) the constitutional factors of a single patient, and 3) the phenotypes and pathophysiology of illness. With examples from research on depressive disorders, we propose solutions and discuss future perspectives, e.g. individual MRI-based electrical field strength as a proxy for NIBS dosage, and also symptoms, their clusters, or biotypes instead of disorder focused NIBS. In conclusion, we propose interleaved research on these three levels along a general track of reverse and forward translation including both clinically directed research in preclinical model systems, and biomarker guided controlled clinical trials. Besides driving the development of safe and efficacious interventions, this framework could also deepen our understanding of psychiatric disorders at their neurophysiological underpinnings.
Collapse
Affiliation(s)
- Frank Padberg
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany
| | - Lucia Bulubas
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany; International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Yuki Mizutani-Tiebel
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany
| | - Gerrit Burkhardt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany
| | - Georg S Kranz
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, SAR, China; Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Max-Planck Institute of Psychiatry, Munich, Germany
| | - Joseph Kambeitz
- Department of Psychiatry, University of Cologne, Faculty of Medicine and University Hospital Cologne, 50937, Germany
| | - Alkomiet Hasan
- Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, University of Augsburg, BKH Augsburg, Dr.-Mack-Str. 1, 86156 Augsburg, Germany; Department of Clinical Radiology, LMU Hospital, Munich, Germany
| | - Shun Takahashi
- Department of Neuropsychiatry, Wakayama Medical University, 811-1 Kimiidera, 6410012 Wakayama, Japan
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany
| | - Stephan Goerigk
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany; Center for Non-invasive Brain Stimulation Munich-Augsburg (CNBS(MA)), Germany; Department of Psychological Methodology and Assessment, Ludwig-Maximilians-University, Leopoldstraße 13, 80802 Munich, Germany; Hochschule Fresenius, University of Applied Sciences, Infanteriestraße 11A, 80797 Munich, Germany
| | - Andre R Brunoni
- Laboratory of Neurosciences (LIM-27), Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo & Hospital Universitário, Universidade de São Paulo, Av. Prof Lineu Prestes 2565, 05508-000 São Paulo, Brazil
| |
Collapse
|
17
|
Baeken C, van Beek V, Vanderhasselt MA, Duprat R, Klooster D. Cortical Thickness in the Right Anterior Cingulate Cortex Relates to Clinical Response to Left Prefrontal Accelerated Intermittent Theta Burst Stimulation: An Exploratory Study. Neuromodulation 2021; 24:938-949. [PMID: 33788975 PMCID: PMC8360012 DOI: 10.1111/ner.13380] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 02/03/2021] [Accepted: 02/15/2021] [Indexed: 12/29/2022]
Abstract
Objectives Accelerated intermittent theta burst stimulation (aiTBS) is a promising treatment option for depressed patients. However, there is a large interindividual variability in clinical effectiveness and individual biomarkers to guide treatment outcome are needed. Materials and Methods Here, the relation between cortical thickness and clinical response (17‐item Hamilton Depression Rating Scale) was studied using anatomical MRI data of 50 depressed patients who were included in a randomized, sham‐controlled, double‐blinded, cross‐over aiTBS design (NCT01832805). Results Baseline cortical thickness in the right caudal part of the anterior cingulate cortex (cACC) was significantly correlated with direct clinical responses in the subgroup who received active aiTBS during the first stimulation week. No correlations were found between baseline cortical thickness and delayed clinical effectiveness. In this particular region, longitudinal changes in cortical thickness were significantly correlated with clinical effectiveness. Furthermore, direct changes in cortical thickness in the right cACC showed predictive potential of delayed clinical responses. Conclusion Cortical thickness within the right cACC might be an important biomarker to predict clinical responses to aiTBS. Additional studies are warranted to substantiate the specific biomarker potential of these parts of the ACC.
Collapse
Affiliation(s)
- Chris Baeken
- Ghent Experimental Psychiatry Laboratory, Ghent University, Ghent, Belgium.,Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Psychiatry, University hospital Brussels, Brussels, Belgium
| | - Vince van Beek
- Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands
| | | | - Romain Duprat
- Department of Psychiatry, Center for the Neuromodulation of Depression and Stress, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Debby Klooster
- Ghent Experimental Psychiatry Laboratory, Ghent University, Ghent, Belgium.,Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| |
Collapse
|
18
|
De Smet S, Baeken C, De Raedt R, Pulopulos MM, Razza LB, Van Damme S, De Witte S, Brunoni AR, Vanderhasselt MA. Effects of combined theta burst stimulation and transcranial direct current stimulation of the dorsolateral prefrontal cortex on stress. Clin Neurophysiol 2021; 132:1116-1125. [PMID: 33773176 DOI: 10.1016/j.clinph.2021.01.025] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 11/26/2020] [Accepted: 01/07/2021] [Indexed: 12/25/2022]
Abstract
OBJECTIVE Research suggests that the combination of different non-invasive brain stimulation techniques, such as intermittent theta-burst stimulation (iTBS) and transcranial direct current stimulation (tDCS), could enhance the effects of stimulation. Studies investigating the combination of tDCS and iTBS over the dorsolateral prefrontal cortex (DLPFC) are lacking. In this within-subjects study, we evaluated the additive effects of iTBS with tDCS on psychophysiological measures of stress. METHOD Sixty-eight healthy individuals were submitted to a bifrontaltDCS + iTBS and shamtDCS + iTBS protocol targeting the DLPFC with a one-week interval. The Maastricht Acute Stress Test was used to activate the stress system after stimulation. Stress reactivity and recovery were assessed using physiological and self-report measures. RESULTS The stressor evoked significant psychophysiological changes in both stimulation conditions. However, no evidence was found for differences between them in stress reactivity and recovery. Participants reported more pain and feelings of discomfort to the bifrontaltDCS + iTBS protocol. CONCLUSION In this study set-up, iTBS plus tDCS was not superior to iTBS in downregulating stress in healthy subjects. SIGNIFICANCE There is no evidence for an effect of combined tDCS-iTBS of the DLPFC on stress according to the parameters employed in our study. Future studies should explore other stimulation parameters, additive approaches and/or neurobiological markers.
Collapse
Affiliation(s)
- Stefanie De Smet
- Department of Head and Skin, Psychiatry and Medical Psychology, Ghent University Hospital, Ghent University, Ghent, Belgium; Ghent Experimental Psychiatry (GHEP) Lab, Ghent, Belgium.
| | - Chris Baeken
- Department of Head and Skin, Psychiatry and Medical Psychology, Ghent University Hospital, Ghent University, Ghent, Belgium; Ghent Experimental Psychiatry (GHEP) Lab, Ghent, Belgium; Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium; Department of Psychiatry, Brussels University Hospital, Brussels, Belgium; Department of Electrical Engineering, Eindhoven University of Technology, the Netherlands.
| | - Rudi De Raedt
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium.
| | - Matias M Pulopulos
- Department of Psychology and Sociology, University of Zaragoza, Aragon, Spain.
| | - Lais B Razza
- Laboratory of Neurosciences (LIM-27), Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo & Hospital Universitário, Universidade de São Paulo, São Paulo, Brazil
| | - Stefaan Van Damme
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium.
| | - Sara De Witte
- Department of Head and Skin, Psychiatry and Medical Psychology, Ghent University Hospital, Ghent University, Ghent, Belgium; Ghent Experimental Psychiatry (GHEP) Lab, Ghent, Belgium.
| | - Andre R Brunoni
- Laboratory of Neurosciences (LIM-27), Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo & Hospital Universitário, Universidade de São Paulo, São Paulo, Brazil
| | - Marie-Anne Vanderhasselt
- Department of Head and Skin, Psychiatry and Medical Psychology, Ghent University Hospital, Ghent University, Ghent, Belgium; Ghent Experimental Psychiatry (GHEP) Lab, Ghent, Belgium; Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium.
| |
Collapse
|
19
|
Overvliet GM, Jansen RAC, van Balkom AJLM, van Campen DC, Oudega ML, van der Werf YD, van Exel E, van den Heuvel OA, Dols A. Adverse events of repetitive transcranial magnetic stimulation in older adults with depression, a systematic review of the literature. Int J Geriatr Psychiatry 2021; 36:383-392. [PMID: 33156540 PMCID: PMC7894543 DOI: 10.1002/gps.5440] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 08/07/2020] [Accepted: 09/16/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVE In the last decade, repetitive transcranial magnetic stimulation (rTMS) has been introduced as a non-invasive neuromodulation therapy for depression. Little is known, however, about (serious) adverse events (AE) of rTMS in older adults with a depression. In this article, we want to study what is known about (serious) AE of rTMS in older adults (>60 years) with late-life depression (LLD). METHODS A systematic search has been performed according to the PRISMA guidelines in PubMed, EMBase and PsycInfo. We have screened 622 articles for eligibility. Eleven studies, evaluating 353 patients in total, were included in this review. RESULTS AE were reported in 12.4% of the older adults with a LLD treated with rTMS, serious AE in 1.5%. Headache (6.9%) and discomfort at the stimulation site (2.7%) are the most commonly reported AE. Serious AE reported are: psychiatric hospitalization (three times), a combination of posterior vitreous detachment and retinal tear, and increased suicide ideation (both once). CONCLUSIONS rTMS in older adults with LLD was concluded overall to be safe due to the low frequency of AE reported in trials and observational studies. In case-reports, however, more serious AE have been described. To tailor use of rTMS in older adults with LLD, more research is needed in larger samples to optimize tolerance.
Collapse
Affiliation(s)
- Geke M. Overvliet
- Department of Old Age PsychiatryGGZ inGeestSpecialized Mental Health CareAmsterdamNetherlands,Department of NeurologyAmsterdam UMClocation VUmcAmsterdam NeuroscienceAmsterdamNetherlands
| | - Rebecca A. C. Jansen
- Department of Old Age PsychiatryGGZ inGeestSpecialized Mental Health CareAmsterdamNetherlands
| | | | - Dilene C. van Campen
- Department of Anatomy & NeurosciencesAmsterdam UMClocation VUmcAmsterdam NeuroscienceAmsterdamNetherlands
| | - Mardien L. Oudega
- Department of Old Age PsychiatryGGZ inGeestSpecialized Mental Health CareAmsterdamNetherlands
| | - Ysbrand D. van der Werf
- Department of Anatomy & NeurosciencesAmsterdam UMClocation VUmcAmsterdam NeuroscienceAmsterdamNetherlands
| | - Eric van Exel
- Department of Old Age PsychiatryGGZ inGeestSpecialized Mental Health CareAmsterdamNetherlands
| | - Odile A. van den Heuvel
- Department of Anatomy & NeurosciencesAmsterdam UMClocation VUmcAmsterdam NeuroscienceAmsterdamNetherlands,Department of PsychiatryAmsterdam UMClocation VUmcAmsterdam NeuroscienceAmsterdamNetherlands
| | - Annemiek Dols
- Department of Old Age PsychiatryGGZ inGeestSpecialized Mental Health CareAmsterdamNetherlands,Department of NeurologyAmsterdam UMClocation VUmcAmsterdam NeuroscienceAmsterdamNetherlands
| |
Collapse
|