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Tao Q, Dang J, Guo H, Zhang M, Niu X, Kang Y, Sun J, Ma L, Wei Y, Wang W, Wen B, Cheng J, Han S, Zhang Y. Abnormalities in static and dynamic intrinsic neural activity and neurotransmitters in first-episode OCD. J Affect Disord 2024; 363:609-618. [PMID: 39029696 DOI: 10.1016/j.jad.2024.07.123] [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: 01/24/2024] [Revised: 06/29/2024] [Accepted: 07/16/2024] [Indexed: 07/21/2024]
Abstract
BACKGROUND Obsessive-compulsive disorder (OCD) is a disabling disorder in which the temporal variability of regional brain connectivity is not well understood. The aim of this study was to investigate alterations in static and dynamic intrinsic neural activity (INA) in first-episode OCD and whether these changes have the potential to reflect neurotransmitters. METHODS A total of 95 first-episode OCD patients and 106 matched healthy controls (HCs) were included in this study. Based on resting-state functional magnetic resonance imaging (rs-fMRI), the static and dynamic local connectivity coherence (calculated by static and dynamic regional homogeneity, sReHo and dReHo) were compared between the two groups. Furthermore, correlations between abnormal INA and PET- and SPECT-derived maps were performed to examine specific neurotransmitter system changes underlying INA abnormalities in OCD. RESULTS Compared with HCs, OCD showed decreased sReHo and dReHo values in left superior, middle temporal gyrus (STG/MTG), left Heschl gyrus (HES), left putamen, left insula, bilateral paracentral lobular (PCL), right postcentral gyrus (PoCG), right precentral gyrus (PreCG), left precuneus and right supplementary motor area (SMA). Decreased dReHo values were also found in left PoCG, left PreCG, left SMA and left middle cingulate cortex (MCC). Meanwhile, alterations in INA present in brain regions were correlated with dopamine system (D2, FDOPA), norepinephrine transporter (NAT) and the vesicular acetylcholine transporter (VAChT) maps. CONCLUSION Static and dynamic INA abnormalities exist in first-episode OCD, having the potential to reveal the molecular characteristics. The results help to further understand the pathophysiological mechanism and provide alternative therapeutic targets of OCD.
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Affiliation(s)
- Qiuying Tao
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Jinghan Dang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Huirong Guo
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, China
| | - Mengzhe Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Xiaoyu Niu
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Yimeng Kang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Jieping Sun
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Longyao Ma
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Baohong Wen
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China.
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China.
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Stephenson C, Philipp-Muller A, Moghimi E, Nashed JY, Cook DJ, Shirazi A, Milev R, Alavi N. Effects of cognitive behavioural therapy and exposure-response prevention on brain activation in obsessive-compulsive disorder patients: systematic review and meta-analysis. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01852-6. [PMID: 38935215 DOI: 10.1007/s00406-024-01852-6] [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: 04/17/2023] [Accepted: 06/17/2024] [Indexed: 06/28/2024]
Abstract
Current psychotherapeutic treatments for OCD, while effective, have complex outcomes with mixed efficacy. Previous research has observed baseline brain activation patterns in OCD patients, elucidating some of the implications of this disorder. Observing the effects of evidence-based psychotherapeutics for OCD on brain activation (through MRI) may provide a more comprehensive outline of pathology. This systematic review and meta-analysis evaluated the effects of cognitive behavioural therapy (CBT) with exposure-response prevention (ERP) on brain activation in OCD patients. Academic databases were systematically searched, and the outcomes evaluated included changes in brain activation and symptom severity between baseline and post-treatment. Patients (n = 193) had confirmed OCD diagnosis and underwent protocolized CBT with ERP programs delivered by trained therapists. Participants in the CBT with ERP programs demonstrated significant improvements in symptom severity (Cohen's d = - 1.91). In general, CBT with ERP resulted in decreased activation post-treatment in the frontal (Cohen's d = 0.40), parietal (Cohen's d = 0.79), temporal (Cohen's d = 1.02), and occipital lobe (Cohen's d = 0.76), and cerebellum (Cohen's d = - 0.78). The findings support CBT with ERP's ability to improve brain activation abnormalities in OCD patients. By identifying regions that improved activation levels, psychotherapy programs may benefit from the addition of function-specific features that could improve treatment outcomes.
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Masjoodi S, Farrokhi M, Afkham BV, Koohsar JS. Advances in DTI studies for diagnoses and treatment of obsessive-compulsive disorder. Psychiatry Res Neuroimaging 2024; 340:111794. [PMID: 38422871 DOI: 10.1016/j.pscychresns.2024.111794] [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: 07/01/2023] [Revised: 11/15/2023] [Accepted: 02/09/2024] [Indexed: 03/02/2024]
Abstract
This review summarizes the current state of neuroimaging research on obsessive-compulsive disorder (OCD) using diffusion tensor imaging (DTI), which allows for the examination of white matter abnormalities in the brain. DTI studies on individuals with obsessive-compulsive disorder (OCD) consistently demonstrate widespread reductions in white matter integrity in various regions of the brain, including the corpus callosum, anterior and posterior cingulate cortex, and prefrontal cortex, which are involved in emotion regulation, decision-making, and cognitive control. However, the reviewed studies often have small sample sizes, and findings vary between studies, highlighting the need for larger and more standardized studies. Furthermore, discerning between causal and consequential effects of OCD on white matter integrity poses a challenge. Addressing this issue may be facilitated through longitudinal studies, including those evaluating the impact of treatment interventions, to enhance the accuracy of DTI data acquisition and processing, thereby improving the validity and comparability of study outcomes. In summary, DTI studies provide valuable insights into the neural circuits and connectivity disruptions in OCD, and future studies may benefit from standardized data analysis and larger sample sizes to determine whether structural abnormalities could be potential biomarkers for early identification and treatment of OCD.
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Affiliation(s)
- Sadegh Masjoodi
- Shiraz Neuroscience Research Center, Shiraz University of Medical Sciences, Shiraz, 7194815644, Iran.
| | - MajidReza Farrokhi
- Shiraz Neuroscience Research Center, Shiraz University of Medical Sciences, Shiraz, 7194815644, Iran; Department of Neurosurgery, School of Medicine, Shiraz University of Medical Sciences, Shiraz, 7194815644, Iran
| | - Behrouz Vejdani Afkham
- NeuroPoly, Inistitute of Biomedical Engineering, Polytechnical Montreal, Montreal, QC, H3T 1J4, Canada
| | - Javad Sheikhi Koohsar
- School of Advanced medical technology, Isfahan University of Medical Sciences, Isfahan, 8415683111, Iran
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4
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Bresser T, Leerssen J, Hölsken S, Groote I, Foster-Dingley JC, van den Heuvel MP, Van Someren EJW. The role of brain white matter in depression resilience and response to sleep interventions. Brain Commun 2023; 5:fcad210. [PMID: 37554956 PMCID: PMC10406158 DOI: 10.1093/braincomms/fcad210] [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: 02/15/2023] [Revised: 06/28/2023] [Accepted: 07/31/2023] [Indexed: 08/10/2023] Open
Abstract
Insomnia poses a high risk for depression. Brain mechanisms of sleep and mood improvement following cognitive behavioural therapy for insomnia remain elusive. This longitudinal study evaluated whether (i) individual differences in baseline brain white matter microstructure predict improvements and (ii) intervention affects brain white matter microstructure. People meeting the Diagnostic and Statistical Manual of Mental Disorders-5 criteria for Insomnia Disorder (n = 117) participated in a randomized controlled trial comparing 6 weeks of no treatment with therapist-guided digital cognitive behavioural therapy for insomnia, circadian rhythm support or their combination (cognitive behavioural therapy for insomnia + circadian rhythm support). Insomnia Severity Index and Inventory of Depressive Symptomatology-Self Report were assessed at baseline and followed up at Weeks 7, 26, 39 and 52. Diffusion-weighted magnetic resonance images were acquired at baseline and Week 7. Skeletonized white matter tracts, fractional anisotropy and mean diffusivity were quantified both tract-wise and voxel-wise using tract-based spatial statistics. Analyses used linear and mixed effect models while correcting for multiple testing using false discovery rate and Bonferroni for correlated endpoint measures. Our results show the following: (i) tract-wise lower fractional anisotropy in the left retrolenticular part of the internal capsule at baseline predicted both worse progression of depressive symptoms in untreated participants and more improvement in treated participants (fractional anisotropy × any intervention, PFDR = 0.053, Pcorr = 0.045). (ii) Only the cognitive behavioural therapy for insomnia + circadian rhythm support intervention induced a trend-level mean diffusivity decrease in the right superior corona radiata (PFDR = 0.128, Pcorr = 0.108), and individuals with a stronger mean diffusivity decrease showed a stronger alleviation of insomnia (R = 0.20, P = 0.035). In summary, individual differences in risk and treatment-supported resilience of depression involve white matter microstructure. Future studies could target the role of the left retrolenticular part of the internal capsule and right superior corona radiata and the brain areas they connect.
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Affiliation(s)
- Tom Bresser
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, 1105 BA, Amsterdam, The Netherlands
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universtiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam Neuroscience, VU University Medical Center, 1081 HV, Amsterdam, The Netherlands
| | - Jeanne Leerssen
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, 1105 BA, Amsterdam, The Netherlands
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universtiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Stefanie Hölsken
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, 1105 BA, Amsterdam, The Netherlands
- Institute of Medical Psychology and Behavioral Immunobiology, University Hospital Essen, University of Duisburg Essen, 45122, Essen, Germany
| | - Inge Groote
- Computational Radiology and Artificial Intelligence (CRAI), Division of Radiology and Nuclear Medicine, Oslo University Hospital, 0372, Oslo, Norway
- Department of Radiology, Vestfold Hospital Trust, 3116, Tønsberg, Norway
| | - Jessica C Foster-Dingley
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, 1105 BA, Amsterdam, The Netherlands
| | - Martijn P van den Heuvel
- Department of Clinical Genetics, Amsterdam Neuroscience, VU University Medical Center, 1081 HV, Amsterdam, The Netherlands
| | - Eus J W Van Someren
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, 1105 BA, Amsterdam, The Netherlands
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, Vrije Universtiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Department of Psychiatry, Vrije Universtiteit Amsterdam, Amsterdam UMC, 1081 HV, Amsterdam, The Netherlands
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5
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Bertolín S, Alonso P, Martínez-Zalacaín I, Menchón JM, Jimenez-Murcia S, Baker JT, Bargalló N, Batistuzzo MC, Boedhoe PSW, Brennan BP, Feusner JD, Fitzgerald KD, Fontaine M, Hansen B, Hirano Y, Hoexter MQ, Huyser C, Jahanshad N, Jaspers-Fayer F, Kuno M, Kvale G, Lazaro L, Machado-Sousa M, Marsh R, Morgado P, Nakagawa A, Norman L, Nurmi EL, O'Neill J, Ortiz AE, Perriello C, Piacentini J, Picó-Pérez M, Shavitt RG, Shimizu E, Simpson HB, Stewart SE, Thomopoulos SI, Thorsen AL, Walitza S, Wolters LH, Thompson PM, van den Heuvel OA, Stein DJ, Soriano-Mas C. Right Prefrontal Cortical Thickness Is Associated With Response to Cognitive-Behavioral Therapy in Children With Obsessive-Compulsive Disorder. J Am Acad Child Adolesc Psychiatry 2023; 62:403-414. [PMID: 36526161 PMCID: PMC10065927 DOI: 10.1016/j.jaac.2022.07.865] [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: 03/13/2022] [Revised: 07/26/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Cognitive-behavioral therapy (CBT) is considered a first-line treatment for obsessive-compulsive disorder (OCD) in pediatric and adult populations. Nevertheless, some patients show partial or null response. The identification of predictors of CBT response may improve clinical management of patients with OCD. Here, we aimed to identify structural magnetic resonance imaging (MRI) predictors of CBT response in 2 large series of children and adults with OCD from the worldwide ENIGMA-OCD consortium. METHOD Data from 16 datasets from 13 international sites were included in the study. We assessed which variations in baseline cortical thickness, cortical surface area, and subcortical volume predicted response to CBT (percentage of baseline to post-treatment symptom reduction) in 2 samples totaling 168 children and adolescents (age range 5-17.5 years) and 318 adult patients (age range 18-63 years) with OCD. Mixed linear models with random intercept were used to account for potential cross-site differences in imaging values. RESULTS Significant results were observed exclusively in the pediatric sample. Right prefrontal cortex thickness was positively associated with the percentage of CBT response. In a post hoc analysis, we observed that the specific changes accounting for this relationship were a higher thickness of the frontal pole and the rostral middle frontal gyrus. We observed no significant effects of age, sex, or medication on our findings. CONCLUSION Higher cortical thickness in specific right prefrontal cortex regions may be important for CBT response in children with OCD. Our findings suggest that the right prefrontal cortex plays a relevant role in the mechanisms of action of CBT in children.
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Affiliation(s)
- Sara Bertolín
- Bellvitge Biomedical Research Institute-IDIBELL, Bellvitge University Hospital, Barcelona, Spain; CIBERSAM, Barcelona, Spain
| | - Pino Alonso
- Bellvitge Biomedical Research Institute-IDIBELL, Bellvitge University Hospital, Barcelona, Spain; CIBERSAM, Barcelona, Spain; University of Barcelona, Barcelona, Spain
| | - Ignacio Martínez-Zalacaín
- Bellvitge Biomedical Research Institute-IDIBELL, Bellvitge University Hospital, Barcelona, Spain; University of Barcelona, Barcelona, Spain
| | - Jose M Menchón
- Bellvitge Biomedical Research Institute-IDIBELL, Bellvitge University Hospital, Barcelona, Spain; CIBERSAM, Barcelona, Spain; University of Barcelona, Barcelona, Spain
| | - Susana Jimenez-Murcia
- Bellvitge Biomedical Research Institute-IDIBELL, Bellvitge University Hospital, Barcelona, Spain; University of Barcelona, Barcelona, Spain; CIBERobn, ISCIII, Spain
| | - Justin T Baker
- McLean Hospital, Belmont, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Nuria Bargalló
- CIBERSAM, Barcelona, Spain; University of Barcelona, Barcelona, Spain; Image Diagnostic Center, Hospital Clinic, Barcelona, Spain; Magnetic Resonance Image Core Facility (IDIBAPS), Barcelona, Spain
| | - Marcelo Camargo Batistuzzo
- Hospital das Clinicas HCFMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil; Pontificial Catholic University of Sao Paulo, Brazil
| | | | - Brian P Brennan
- McLean Hospital, Belmont, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Jamie D Feusner
- University of California Los Angeles, Los Angeles, California; University of Toronto, Canada; Centre for Addiction and Mental Health, Toronto, Canada; Karolinksa Institutet, Stockholm, Sweden
| | - Kate D Fitzgerald
- Columbia University, New York; The New York State Psychiatric Institute, New York
| | - Martine Fontaine
- Columbia University Medical College, Columbia University, New York
| | - Bjarne Hansen
- Bergen Center for Brain Plasticity, Haukeland University Hospital, Bergen, Norway; Centre for Crisis Psychology, University of Bergen, Bergen, Norway
| | - Yoshiyuki Hirano
- Research Center for Child Mental Development, Chiba University, Chiba, Japan; United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan
| | - Marcelo Q Hoexter
- Hospital das Clinicas HCFMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil; LiNC - Laboratory of Integrative Neuroscience of Universidade Federal de São Paulo (UNIFESP), Brazil
| | - Chaim Huyser
- Levvel, Academic Center for Child and Adolescent Psychiatry, Amsterdam, the Netherlands; Amsterdam UMC, Amsterdam, the Netherlands
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California
| | - Fern Jaspers-Fayer
- University of British Columbia, Vancouver, Canada; British Columbia Children's Hospital Research Institute, Vancouver, Canada
| | - Masaru Kuno
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
| | - Gerd Kvale
- Bergen Center for Brain Plasticity, Haukeland University Hospital, Bergen, Norway; University of Bergen, Bergen, Norway
| | - Luisa Lazaro
- CIBERSAM, Barcelona, Spain; University of Barcelona, Barcelona, Spain; IDIBAPS, Barcelona, Spain; Hospital Clínic, Barcelona, Spain
| | - Mafalda Machado-Sousa
- Life and Health Sciences Research Institute (ICVS), University of Minho, Braga, Portugal; ICVS/3B's, PT Government Associate Laboratory, Braga/Guimarães, Portugal; Clinical Academic Center - Braga, Braga, Portugal
| | - Rachel Marsh
- The New York State Psychiatric Institute, New York; Columbia University Medical College, Columbia University, New York
| | - Pedro Morgado
- Life and Health Sciences Research Institute (ICVS), University of Minho, Braga, Portugal; ICVS/3B's, PT Government Associate Laboratory, Braga/Guimarães, Portugal; Clinical Academic Center - Braga, Braga, Portugal
| | - Akiko Nakagawa
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
| | | | - Erika L Nurmi
- University of California Los Angeles, Los Angeles, California
| | - Joseph O'Neill
- UCLA Division of Child and Adolescent Psychiatry, Los Angeles, California; UCLA Brain Research Institute, Los Angeles, California
| | - Ana E Ortiz
- IDIBAPS, Barcelona, Spain; Hospital Clínic, Barcelona, Spain
| | - Chris Perriello
- University of Illinois at Urbana Champaign, Champaign, Illinois
| | - John Piacentini
- UCLA Division of Child and Adolescent Psychiatry, Los Angeles, California; UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, California
| | - Maria Picó-Pérez
- Life and Health Sciences Research Institute (ICVS), University of Minho, Braga, Portugal; ICVS/3B's, PT Government Associate Laboratory, Braga/Guimarães, Portugal; Clinical Academic Center - Braga, Braga, Portugal
| | - Roseli G Shavitt
- Hospital das Clinicas HCFMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Eiji Shimizu
- Research Center for Child Mental Development, Chiba University, Chiba, Japan; United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan
| | - Helen Blair Simpson
- The New York State Psychiatric Institute, New York; Columbia University Medical College, Columbia University, New York
| | - S Evelyn Stewart
- University of British Columbia, Vancouver, Canada; British Columbia Children's Hospital Research Institute, Vancouver, Canada; British Columbia Mental Health and Substance Use Services Research Institute, Vancouver, Canada
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California
| | - Anders Lillevik Thorsen
- Bergen Center for Brain Plasticity, Haukeland University Hospital, Bergen, Norway; Centre for Crisis Psychology, University of Bergen, Bergen, Norway
| | - Susanne Walitza
- University Hospital of Psychiatry Zurich, University of Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland
| | - Lidewij H Wolters
- Levvel, Academic Center for Child and Adolescent Psychiatry, Amsterdam, the Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Dan J Stein
- SAMRC Unit on Risk and Resilience in Mental Disorders, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Carles Soriano-Mas
- Bellvitge Biomedical Research Institute-IDIBELL, Bellvitge University Hospital, Barcelona, Spain; CIBERSAM, Barcelona, Spain; University of Barcelona, Barcelona, Spain.
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Poli A, Pozza A, Orrù G, Conversano C, Ciacchini R, Pugi D, Angelo NL, Angeletti LL, Miccoli M, Gemignani A. Neurobiological outcomes of cognitive behavioral therapy for obsessive-compulsive disorder: A systematic review. Front Psychiatry 2022; 13:1063116. [PMID: 36569616 PMCID: PMC9780289 DOI: 10.3389/fpsyt.2022.1063116] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 11/22/2022] [Indexed: 12/13/2022] Open
Abstract
Introduction Obsessive-compulsive disorder (OCD) is characterized by recurrent distressing thoughts and repetitive behaviors, or mental rituals performed to reduce anxiety. Recent neurobiological techniques have been particularly convincing in suggesting that cortico-striatal-thalamic-cortico (CSTC) circuits, including orbitofrontal cortex (OFC) and striatum regions (caudate nucleus and putamen), are responsible for mediation of OCD symptoms. However, it is still unclear how these regions are affected by OCD treatments in adult patients. To address this yet open question, we conducted a systematic review of all studies examining neurobiological changes before and after first-line psychological OCD treatment, i.e., cognitive-behavioral therapy (CBT). Methods Studies were included if they were conducted in adults with OCD and they assessed the neurobiological effects of CBT before and after treatment. Two databases were searched: PsycINFO and PubMed for the time frame up to May 2022. Results We obtained 26 pre-post CBT treatment studies performed using different neurobiological techniques, namely functional magnetic resonance imaging (fMRI), Positron emission tomography (PET), regional cerebral blood flow (rCBF), 5-HT concentration, magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), Electroencephalography (EEG). Neurobiological data show the following after CBT intervention: (i) reduced activations in OFC across fMRI, EEG, and rCBF; (ii) decreased activity in striatum regions across fMRI, rCBF, PET, and MRI; (iii) increased activations in cerebellum (CER) across fMRI and MRI; (iv) enhanced neurochemical concentrations in MRS studies in OFC, anterior cingulate cortex (ACC) and striatum regions. Most of these neurobiological changes are also accompanied by an improvement in symptom severity as assessed by a reduction in the Y-BOCS scores. Conclusion Cognitive-behavioral therapy seems to be able to restructure, modify, and transform the neurobiological component of OCD, in addition to the clinical symptoms. Nevertheless, further studies are necessary to frame the OCD spectrum in a dimensional way.
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Affiliation(s)
- Andrea Poli
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Andrea Pozza
- Department of Medical Sciences, Surgery, and Neurosciences, University of Siena, Siena, Italy
| | - Graziella Orrù
- Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy
| | - Ciro Conversano
- Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy
| | - Rebecca Ciacchini
- Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy
| | - Daniele Pugi
- Department of Medical Sciences, Surgery, and Neurosciences, University of Siena, Siena, Italy
| | - Nicole Loren Angelo
- Department of Medical Sciences, Surgery, and Neurosciences, University of Siena, Siena, Italy
| | | | - Mario Miccoli
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Angelo Gemignani
- Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy
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Yu WR, Jhang JF, Chen BY, Ou SR, Li HM, Kuo HC. Multimodal Treatment with Cognitive Behavioral Therapeutic Intervention Plus Bladder Treatment Is More Effective than Monotherapy for Patients with Interstitial Cystitis/Bladder Pain Syndrome-A Randomized Clinical Trial. J Clin Med 2022; 11:6221. [PMID: 36294541 PMCID: PMC9604893 DOI: 10.3390/jcm11206221] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 10/10/2022] [Accepted: 10/20/2022] [Indexed: 11/16/2022] Open
Abstract
(1) Background: Introduction: Interstitial cystitis/bladder pain syndrome (IC/BPS) not only induces physiological damage but also greatly affects psychological stress. Multidisciplinary therapy has been recommended for IC/BPS treatment, but clinical trial data of combined bladder therapy and cognitive behavioral therapy (CBT) are lacking. This study evaluated CBT efficacy in patients with IC/BPS. (2) Methods: Patients with IC/BPS were randomized to the bladder monotherapy (BT) or combined CBT (CBT) group. The primary endpoint was the self-reported outcome by global response assessment (GRA). Secondary endpoints included IC symptoms and problem index, bladder pain score, Beck’s anxiety inventory (BAI), and depression inventory, and objective parameters were also compared. (3) Result: A total of 30 patients receiving BT and 30 receiving CBT therapy were enrolled. Significant improvement of the BAI at 8 (p = 0.045) and 12 weeks (p = 0.02) post-treatment was observed in the CBT group, with significantly greater GRA scores at 12 weeks (p < 0.001). Repeated measures analysis of variance showed a significant effect within the CBT group on IC/BPS patients’ self-reported treatment outcomes (p = 0.001) and anxiety severity BAI scores (p = 0.033). (4) Conclusion: A multimodal treatment of CBT combined with suitable bladder treatment more effectively improves anxiety severity and treatment outcomes in patients with IC/BPS.
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Affiliation(s)
- Wan-Ru Yu
- Department of Nursing, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 970, Taiwan
- Institute of Medical Sciences, Tzu Chi University, Hualien 970, Taiwan
- Department of Urology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien 970, Taiwan
| | - Jia-Fong Jhang
- Department of Urology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien 970, Taiwan
| | - Bai-Yueh Chen
- Department of Psychiatry, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 970, Taiwan
| | - Syuan-Ru Ou
- Department of Nursing, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 970, Taiwan
| | - Hao-Ming Li
- Department of Psychiatry, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien 970, Taiwan
| | - Hann-Chorng Kuo
- Department of Urology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien 970, Taiwan
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8
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Static and temporal dynamic changes of intrinsic brain activity in pediatric and adults OCD. J Affect Disord 2022; 311:416-424. [PMID: 35618169 DOI: 10.1016/j.jad.2022.05.101] [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: 12/13/2021] [Revised: 04/29/2022] [Accepted: 05/16/2022] [Indexed: 11/24/2022]
Abstract
Epidemiological and clinical age differences in obsessive-compulsive disorder (OCD) have been reported in clinical symptoms and morphometry changes; however, age differences in amplitude of low-frequency fluctuation and the relationship between ALFF imaging and clinical symptoms has not been thoroughly studied in OCD. Age may be an important feature associated with distinct subtypes of OCD. To examine the effect of age on OCD, the current study enrolled 92 OCD patients (32 pediatrics and 60 adults) and matched HCs (33 pediatrics and 84 adults), undergoing resting-state functional magnetic resonance imaging. The spontaneous brain activity was measured by static and dynamic amplitude of low-frequency fluctuation (ALFF) followed by two-way ANOVA. In pediatric OCD patients versus adult patients, we observed a significantly higher ALFF in the default mode network (DMN), including posterior cingulate, precuneus and superior frontal gyrus, and extending to cuneus, lingual gyrus. Additionally, the increased ALFF and dynamic ALFF in the precentral gyrus were found in pediatric patients. In OCD patients compared with controls, we found a significantly increased ALFF in hippocampal gyrus, cerebellum network (CN), and the dALFF in middle and inferior occipital gyrus, bilateral paracentral lobule and sensorimotor network. The findings emphasized the different patterns of static and dynamic intrinsic brain activity alterations associated with pediatric and adult OCD patients. These results provide unique insights into constructing evidenced-based distinct OCD subtypes based on brain activity and point the need of specified management for pediatric and adult OCD patients in clinical setting.
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9
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Comprehensive Cortical Structural Features Predict the Efficacy of Cognitive Behavioral Therapy in Obsessive-Compulsive Disorder. Brain Sci 2022; 12:brainsci12070921. [PMID: 35884728 PMCID: PMC9322050 DOI: 10.3390/brainsci12070921] [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: 05/31/2022] [Revised: 06/30/2022] [Accepted: 07/09/2022] [Indexed: 12/10/2022] Open
Abstract
Although cognitive behavioral therapy (CBT) is effective for patients with obsessive-compulsive disorder (OCD), 40% of OCD patients show a poor response to CBT. This study aimed to identify the cortical structural factors that predict CBT outcomes in OCD patients. A total of 56 patients with OCD received baseline structural MRI (sMRI) scanning and 14 individual CBT sessions. The linear support vector regression (SVR) models were used to identify the predictive performance of sMRI indices, including gray matter volume, cortical thickness, sulcal depth, and gyrification value. The patients’ OC symptoms decreased significantly after CBT intervention (p < 0.001). We found the model with the comprehensive variables exhibited better performance than the models with single structural indices (MAE = 0.14, MSE = 0.03, R2 = 0.36), showing a significant correlation between the true value and the predicted value (r = 0.63, p < 0.001). The results indicated that a model integrating four cortical structural features can accurately predict the effectiveness of CBT for OCD. Future models incorporating other brain indicators, including brain functional indicators, EEG indicators, neurotransmitters, etc., which might be more accurate for predicting the effectiveness of CBT for OCD, are needed.
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10
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Li X, Li H, Cao L, Liu J, Xing H, Huang X, Gong Q. Application of graph theory across multiple frequency bands in drug-naïve obsessive-compulsive disorder with no comorbidity. J Psychiatr Res 2022; 150:272-278. [PMID: 35427825 DOI: 10.1016/j.jpsychires.2022.03.041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 03/14/2022] [Accepted: 03/24/2022] [Indexed: 10/18/2022]
Abstract
Recently, graph theoretical analysis based on resting-state functional magnetic resonance imaging has provided a means of investigating the complex brain connectome in obsessive-compulsive disorder (OCD) patients. However, these studies have been restricted to spontaneous blood oxygen level-dependent (BOLD) signals with frequency bands between 0.01 and 0.08 Hz, and the parameters from graph theory across multiple frequency bands have seldom been studied. Here, we calculated global metrics (small-worldness, global efficiency and modularity) and nodal metrics (degree centrality, betweenness centrality, nodal clustering coefficient and shortest path) at four different frequency bands (slow-2 (0.199-0.25 Hz), slow-3 (0.074-0.198 Hz), slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz), from 0.01 to 0.25 Hz) in seventy-three OCD patients and ninety healthy controls. The analyses were also calculated in traditional low-frequency bands (0.01-0.08 Hz) for reference. For the global metrics, the OCD patients showed increased small-worldness and modularity only in the slow-3 band. For the local metrics, we observed a frequency-dependent characteristic, with the main significant differences in regions including the right precentral gyrus, occipital region, right anterior cingulum cortex and fusiform cortex. Our results suggested frequency-specific abnormalities of the brain connectome in OCD and the future studies may need to consider different frequency bands when measuring spontaneous activity in the brain.
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Affiliation(s)
- Xue Li
- College of Physics, Sichuan University, Chengdu, PR China; Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, PR China
| | - Hailong Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, PR China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, PR China
| | - Lingxiao Cao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, PR China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, PR China
| | - Jing Liu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, PR China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, PR China
| | - Haoyang Xing
- College of Physics, Sichuan University, Chengdu, PR China; Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, PR China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, PR China.
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, PR China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, PR China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, PR China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, PR China
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11
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Mackiewicz Seghete KL, Filbey FM, Hudson KA, Hyun B, Feldstein Ewing SW. Time for a paradigm shift: The adolescent brain in addiction treatment. Neuroimage Clin 2022; 34:102960. [PMID: 35172248 PMCID: PMC8850747 DOI: 10.1016/j.nicl.2022.102960] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 12/29/2021] [Accepted: 02/06/2022] [Indexed: 11/02/2022]
Abstract
OBJECTIVE One route to improve adolescent addiction treatment outcomes is to use translational approaches to help identify developmental neuroscience mechanisms that undergird active treatment ingredients and advance adolescent behavior change. METHODS This sample included 163 adolescents (ages 15-19) randomized to motivational interviewing (MI) vs. brief adolescent mindfulness (BAM). Youth completed an fMRI paradigm assessing adolescent brain response to therapist language (complex reflection vs. mindful; complex reflection vs. confront; mindful vs. confront) at pre- (prior to the completion of the full intervention) and post-treatment (at 3-month follow-up) and behavioral measures at 3, 6 and 12 months. RESULTS Youth in both treatment groups showed significant problem drinking reductions at 3 and 6 months, but MI youth demonstrated significantly better treatment outcomes than BAM youth at 12 months. We observed several significant treatment group differences (MI > BAM) in neural response to therapist language, including at pre-treatment when examining complex reflection vs. mindful, and complex reflection vs. confront (e.g., superior temporal gyrus, lingual gyrus); and at post-treatment when examining mindful vs. confront (e.g., supplementary motor area; middle frontal gyrus). When collapsed across treatment groups (MI + BAM), we observed significant differences by time, with youth showing a pattern of brain change in response to complex reflection vs. mindful, and complex reflection vs. confront (e.g., precuneus; postcentral gyrus). There was no evidence of a significant group × time interaction. However, brain change in response to therapist language (complex reflection vs. confront) in regions such as middle frontal gyrus, was associated with reductions in problem drinking at 12 months. Yet, few treatment group differences were observed. CONCLUSIONS These data underscore the need to better understand therapist language and it's impact on the developing brain, in order to inform and aggregate the most impactful elements of addiction treatment for future treatment development for adolescents.
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Affiliation(s)
- Kristen L Mackiewicz Seghete
- Oregon Health & Science University, Department of Psychiatry, 3181 SW Sam Jackson Park Rd, M/C UHN80R1, Portland, OR 97239, USA.
| | - Francesca M Filbey
- Center for BrainHealth, School of Behavioral and Brain Sciences, The University of Texas at Dallas, 2200 West Mockingbird Lane, Dallas, TX 75235, USA.
| | - Karen A Hudson
- Departments of Psychology and Interdisciplinary Neuroscience, University of Rhode Island, 130 Flagg Rd, Kingston, RI 02881 USA.
| | - Benedict Hyun
- Departments of Psychology and Interdisciplinary Neuroscience, University of Rhode Island, 130 Flagg Rd, Kingston, RI 02881 USA.
| | - Sarah W Feldstein Ewing
- Departments of Psychology and Interdisciplinary Neuroscience, University of Rhode Island, 130 Flagg Rd, Kingston, RI 02881 USA.
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12
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Zhang F, Daducci A, He Y, Schiavi S, Seguin C, Smith RE, Yeh CH, Zhao T, O'Donnell LJ. Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review. Neuroimage 2022; 249:118870. [PMID: 34979249 PMCID: PMC9257891 DOI: 10.1016/j.neuroimage.2021.118870] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 12/03/2021] [Accepted: 12/31/2021] [Indexed: 12/13/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.
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Affiliation(s)
- Fan Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
| | | | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | - Caio Seguin
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia; The University of Sydney, School of Biomedical Engineering, Sydney, Australia
| | - Robert E Smith
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia
| | - Chun-Hung Yeh
- Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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13
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Qin Z, Liang HB, Li M, Hu Y, Wu J, Qiao Y, Liu JR, Du X. Disrupted White Matter Functional Connectivity With the Cerebral Cortex in Migraine Patients. Front Neurosci 2022; 15:799854. [PMID: 35095401 PMCID: PMC8793828 DOI: 10.3389/fnins.2021.799854] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 12/23/2021] [Indexed: 11/18/2022] Open
Abstract
Background: In attempts to understand the migraine patients’ overall brain functional architecture, blood oxygenation level-dependent (BOLD) signals in the white matter (WM) and gray matter (GM) were considered in the current study. Migraine, a severe and multiphasic brain condition, is characterized by recurrent attacks of headaches. BOLD fluctuations in a resting state exhibit similar temporal and spectral profiles in both WM and GM. It is feasible to explore the functional interactions between WM tracts and GM regions in migraine. Methods: Forty-eight migraineurs without aura (MWoA) and 48 healthy controls underwent resting-state functional magnetic resonance imaging. Pearson’s correlations between the mean time courses of 48 white matter (WM) bundles and 82 gray matter (GM) regions were computed for each subject. Two-sample t-tests were performed on the Pearson’s correlation coefficients (CC) to compare the differences between the MWoA and healthy controls in the GM-averaged CC of each bundle and the WM-averaged CC of each GM region. Results: The MWoAs exhibited an overall decreased average temporal CC between BOLD signals in 82 GM regions and 48 WM bundles compared with healthy controls, while little was increased. In particular, WM bundles such as left anterior corona radiata, left external capsule and bilateral superior longitudinal fasciculus had significantly decreased mean CCs with GM in MWoA. On the other hand, 16 GM regions had significantly decreased mean CCs with WM in MWoA, including some areas that are parts of the somatosensory regions, auditory cortex, temporal areas, frontal areas, cingulate cortex, and parietal cortex. Conclusion: Decreased functional connections between WM bundles and GM regions might contribute to disrupted functional connectivity between the parts of the pain processing pathway in MWoAs, which indicated that functional and connectivity abnormalities in cortical regions may not be limited to GM regions but are instead associated with functional abnormalities in WM tracts.
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Affiliation(s)
- Zhaoxia Qin
- School of Psychology, Shanghai University of Sport, Shanghai, China
- Department of Medical Imaging, The Affiliated Hospital of Yangzhou University, Yangzhou, China
| | - Huai-Bin Liang
- Department of Neurology, Jiuyuan Municipal Stroke Center, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Muwei Li
- Vanderbilt University Institute of Imaging Science, Nashville, TN, United States
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Yue Hu
- Department of Neurology, Jiuyuan Municipal Stroke Center, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jing Wu
- Department of Neurology, Jiuyuan Municipal Stroke Center, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuan Qiao
- Department of Neurology, Jiuyuan Municipal Stroke Center, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jian-Ren Liu
- Department of Neurology, Jiuyuan Municipal Stroke Center, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Research Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Jian-Ren Liu,
| | - Xiaoxia Du
- School of Psychology, Shanghai University of Sport, Shanghai, China
- Xiaoxia Du,
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14
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Shephard E, Batistuzzo MC, Hoexter MQ, Stern ER, Zuccolo PF, Ogawa CY, Silva RM, Brunoni AR, Costa DL, Doretto V, Saraiva L, Cappi C, Shavitt RG, Simpson HB, van den Heuvel OA, Miguel EC. Neurocircuit models of obsessive-compulsive disorder: limitations and future directions for research. REVISTA BRASILEIRA DE PSIQUIATRIA 2021; 44:187-200. [PMID: 35617698 PMCID: PMC9041967 DOI: 10.1590/1516-4446-2020-1709] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 03/05/2021] [Indexed: 11/22/2022]
Affiliation(s)
- Elizabeth Shephard
- Universidade de São Paulo (USP), Brazil; Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King’s College London, UK
| | - Marcelo C. Batistuzzo
- Universidade de São Paulo (USP), Brazil; Pontifícia Universidade Católica de São Paulo, Brazil
| | | | - Emily R. Stern
- The New York University School of Medicine, USA; Orangeburg, USA
| | | | | | | | | | | | | | | | - Carolina Cappi
- Universidade de São Paulo (USP), Brazil; Icahn School of Medicine at Mount Sinai, USA
| | | | - H. Blair Simpson
- New York State Psychiatric Institute, Columbia University Irving Medical Center (CUIMC), USA; CUIMC, USA
| | - Odile A. van den Heuvel
- Vrije Universiteit Amsterdam, The Netherlands; Vrije Universiteit Amsterdam, The Netherlands
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15
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Liloia D, Mancuso L, Uddin LQ, Costa T, Nani A, Keller R, Manuello J, Duca S, Cauda F. Gray matter abnormalities follow non-random patterns of co-alteration in autism: Meta-connectomic evidence. Neuroimage Clin 2021; 30:102583. [PMID: 33618237 PMCID: PMC7903137 DOI: 10.1016/j.nicl.2021.102583] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 12/15/2020] [Accepted: 01/30/2021] [Indexed: 02/06/2023]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by atypical brain anatomy and connectivity. Graph-theoretical methods have mainly been applied to detect altered patterns of white matter tracts and functional brain activation in individuals with ASD. The network topology of gray matter (GM) abnormalities in ASD remains relatively unexplored. METHODS An innovative meta-connectomic analysis on voxel-based morphometry data (45 experiments, 1,786 subjects with ASD) was performed in order to investigate whether GM variations can develop in a distinct pattern of co-alteration across the brain. This pattern was then compared with normative profiles of structural and genetic co-expression maps. Graph measures of centrality and clustering were also applied to identify brain areas with the highest topological hierarchy and core sub-graph components within the co-alteration network observed in ASD. RESULTS Individuals with ASD exhibit a distinctive and topologically defined pattern of GM co-alteration that moderately follows the structural connectivity constraints. This was not observed with respect to the pattern of genetic co-expression. Hub regions of the co-alteration network were mainly left-lateralized, encompassing the precuneus, ventral anterior cingulate, and middle occipital gyrus. Regions of the default mode network appear to be central in the topology of co-alterations. CONCLUSION These findings shed new light on the pathobiology of ASD, suggesting a network-level dysfunction among spatially distributed GM regions. At the same time, this study supports pathoconnectomics as an insightful approach to better understand neuropsychiatric disorders.
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Affiliation(s)
- Donato Liloia
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Lorenzo Mancuso
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, FL, USA; Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA.
| | - Tommaso Costa
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), Turin, Italy.
| | - Andrea Nani
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Roberto Keller
- Adult Autism Center, DSM Local Health Unit, ASL TO, Turin, Italy.
| | - Jordi Manuello
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Sergio Duca
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), Turin, Italy.
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