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Asch RH, Abdallah CG, Carson RE, Esterlis I. Challenges and rewards of in vivo synaptic density imaging, and its application to the study of depression. Neuropsychopharmacology 2024:10.1038/s41386-024-01913-3. [PMID: 39039139 DOI: 10.1038/s41386-024-01913-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 06/14/2024] [Accepted: 06/26/2024] [Indexed: 07/24/2024]
Abstract
The development of novel radiotracers for Positron Emission Tomography (PET) imaging agents targeting the synaptic vesicle glycoprotein 2 A (SV2A), an integral glycoprotein present in the membrane of all synaptic vesicles throughout the central nervous system, provides a method for the in vivo quantification of synaptic density. This is of particular interest in neuropsychiatric disorders given that synaptic alterations appear to underlie disease progression and symptom severity. In this review, we briefly describe the development of these SV2A tracers and the evaluation of quantification methods. Next, we discuss application of SV2A PET imaging to the study of depression, including a review of our findings demonstrating lower SV2A synaptic density in people with significant depressive symptoms and the use of a ketamine drug challenge to examine synaptogenesis in vivo. We then highlight the importance of performing translational PET imaging in animal models in conjunction with clinical imaging. We consider the ongoing challenges, possible solutions, and present preliminary findings from our lab demonstrating the translational benefit and potential of in vivo SV2A imaging in animal models of chronic stress. Finally, we discuss methodological improvements and future directions for SV2A imaging, potentially in conjunction with other neural markers.
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Affiliation(s)
- Ruth H Asch
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Chadi G Abdallah
- Menninger Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Richard E Carson
- Department of Radiology and Biomedical Imaging, Yale Positron Emission Tomography Center, Yale School of Medicine, New Haven, CT, USA
- Department of Biomedical Engineering, Yale School of Engineering, New Haven, CT, USA
| | - Irina Esterlis
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- Department of Radiology and Biomedical Imaging, Yale Positron Emission Tomography Center, Yale School of Medicine, New Haven, CT, USA.
- U.S. Department of Veteran Affairs National Center for Posttraumatic Stress Disorder, Clinical Neurosciences Division, VA Connecticut Healthcare System, West Haven, CT, USA.
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2
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Lv Q, Wang X, Lin P, Wang X. Neuromelanin-sensitive magnetic resonance imaging in the study of mental disorder: A systematic review. Psychiatry Res Neuroimaging 2024; 339:111785. [PMID: 38325165 DOI: 10.1016/j.pscychresns.2024.111785] [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: 08/17/2023] [Revised: 11/26/2023] [Accepted: 01/08/2024] [Indexed: 02/09/2024]
Abstract
Dopamine and norepinephrine are implicated in the pathophysiology of mental disorders, but non-invasive study of their neuronal function remains challenging. Recent research suggests that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) techniques may overcome this limitation by enabling the non-invasive imaging of the substantia nigra (SN)/ ventral tegmental area (VTA) dopaminergic and locus coeruleus (LC) noradrenergic systems. A review of 19 studies that met the criteria for NM-MRI application in mental disorders found that despite the use of heterogeneous sequence parameters and metrics, nearly all studies reported differences in contrast ratio (CNR) of LC or SN/VTA between patients with mental disorders and healthy controls. These findings suggest that NM-MRI is a valuable tool in psychiatry, but the differences in sequence parameters across studies hinder comparability, and a standardized analysis pipeline is needed to improve the reliability of results. Further research using standardized methods is needed to better understand the role of dopamine and norepinephrine in mental disorders.
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Affiliation(s)
- Qiuyu Lv
- Department of Psychology and Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, 410081, China; Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, 410081, China
| | - Xuanyi Wang
- Department of Psychology and Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, 410081, China; Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, 410081, China
| | - Pan Lin
- Department of Psychology and Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, 410081, China; Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, 410081, China
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China.; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China..
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3
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Chen Q, Zhong Y, Jin C, Zhou R, Dou X, Yu C, Wang J, Xu H, Tian M, Zhang H. Nuclear psychiatric imaging: the trend of precise diagnosis for mental disorders. Eur J Nucl Med Mol Imaging 2024; 51:1002-1006. [PMID: 38085344 DOI: 10.1007/s00259-023-06519-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Affiliation(s)
- Qiaozhen Chen
- Department of Psychiatry, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yan Zhong
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Chentao Jin
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Xiaofeng Dou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Congcong Yu
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Jing Wang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Han Xu
- Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Mei Tian
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China.
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China.
- Human Phenome Institute, Fudan University, 825 Zhangheng Road, Shanghai, 201203, China.
| | - Hong Zhang
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Zhejiang, 310009, Hangzhou, China.
- Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China.
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
- Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou, 310058, China.
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Ramasubbu R, Brown EC, Mouches P, Moore JA, Clark DL, Molnar CP, Kiss ZHT, Forkert ND. Multimodal imaging measures in the prediction of clinical response to deep brain stimulation for refractory depression: A machine learning approach. World J Biol Psychiatry 2024; 25:175-187. [PMID: 38185882 DOI: 10.1080/15622975.2023.2300795] [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: 09/07/2023] [Accepted: 12/27/2023] [Indexed: 01/09/2024]
Abstract
OBJECTIVES This study compared machine learning models using unimodal imaging measures and combined multi-modal imaging measures for deep brain stimulation (DBS) outcome prediction in treatment resistant depression (TRD). METHODS Regional brain glucose metabolism (CMRGlu), cerebral blood flow (CBF), and grey matter volume (GMV) were measured at baseline using 18F-fluorodeoxy glucose (18F-FDG) positron emission tomography (PET), arterial spin labelling (ASL) magnetic resonance imaging (MRI), and T1-weighted MRI, respectively, in 19 patients with TRD receiving subcallosal cingulate (SCC)-DBS. Responders (n = 9) were defined by a 50% reduction in HAMD-17 at 6 months from the baseline. Using an atlas-based approach, values of each measure were determined for pre-selected brain regions. OneR feature selection algorithm and the naïve Bayes model was used for classification. Leave-out-one cross validation was used for classifier evaluation. RESULTS The performance accuracy of the CMRGlu classification model (84%) was greater than CBF (74%) or GMV (74%) models. The classification model using the three image modalities together led to a similar accuracy (84%0 compared to the CMRGlu classification model. CONCLUSIONS CMRGlu imaging measures may be useful for the development of multivariate prediction models for SCC-DBS studies for TRD. The future of multivariate methods for multimodal imaging may rest on the selection of complementing features and the developing better models.Clinical Trial Registration: ClinicalTrials.gov (#NCT01983904).
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Affiliation(s)
- Rajamannar Ramasubbu
- Department of Psychiatry, Clinical Neurosciences, Mathison Centre for Mental Health Research & Education, Calgary, Alberta, Canada
- Hotchkiss Brain Institute Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Elliot C Brown
- School of Health and Care Management, Arden University, Berlin, Germany
| | - Pauline Mouches
- Department of Radiology, Clinical Neurosciences, Hotchkiss Brain Institute, Cumming school of medicine, University of Calgary, Calgary, Alberta, Canada
| | - Jasmine A Moore
- Department of Radiology, Clinical Neurosciences, Hotchkiss Brain Institute, Cumming school of medicine, University of Calgary, Calgary, Alberta, Canada
| | - Darren L Clark
- Department of Psychiatry, Clinical Neurosciences, Mathison Centre for Mental Health Research & Education, Calgary, Alberta, Canada
- Hotchkiss Brain Institute Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Christine P Molnar
- Department of Radiology, Cumming school of medicine, University of Calgary, Calgary, Alberta, Canada
| | - Zelma H T Kiss
- Department of Psychiatry, Clinical Neurosciences, Mathison Centre for Mental Health Research & Education, Calgary, Alberta, Canada
- Hotchkiss Brain Institute Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Nils D Forkert
- Department of Radiology, Clinical Neurosciences, Hotchkiss Brain Institute, Cumming school of medicine, University of Calgary, Calgary, Alberta, Canada
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5
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Vogel AC, Black KJ. Brain Imaging in Routine Psychiatric Practice. MISSOURI MEDICINE 2024; 121:37-43. [PMID: 38404436 PMCID: PMC10887461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Technologies in the 21st century provide increasingly detailed and accurate maps of brain structure and function. So why don't psychiatrists order brain imaging on all our patients? Here we briefly review major neuroimaging methods and some of their findings in psychiatry. As clinicians and neuroimaging researchers, we are eager to bring brain imaging into daily clinical practice. However, to be clinically useful, any test in medicine must demonstrate adequate test statistics, and show proven benefits that outweigh its risks and costs. In 2024, beyond certain limited circumstances, we have no imaging tests that can meet those standards to provide diagnosis or guide treatment. This cold fact explains why for most psychiatric patients, neuroimaging is not currently recommended by professional organizations or the National Institute of Mental Health.
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Affiliation(s)
- Alecia C Vogel
- Assistant Professor of Psychiatry (Child), Washington University School of Medicine in St. Louis, Missouri
| | - Kevin J Black
- Professor of Psychiatry, Neurology, Radiology, and Neuroscience at Washington University School of Medicine in St. Louis, Missouri
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Jané P, Xu X, Taelman V, Jané E, Gariani K, Dumont RA, Garama Y, Kim F, Del Val Gomez M, Walter MA. The Imageable Genome. Nat Commun 2023; 14:7329. [PMID: 37957176 PMCID: PMC10643363 DOI: 10.1038/s41467-023-43123-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 11/01/2023] [Indexed: 11/15/2023] Open
Abstract
Understanding human disease on a molecular level, and translating this understanding into targeted diagnostics and therapies are central tenets of molecular medicine1. Realizing this doctrine requires an efficient adaptation of molecular discoveries into the clinic. We present an approach to facilitate this process by describing the Imageable Genome, the part of the human genome whose expression can be assessed via molecular imaging. Using a deep learning-based hybrid human-AI pipeline, we bridge individual genes and their relevance in human diseases with specific molecular imaging methods. Cross-referencing the Imageable Genome with RNA-seq data from over 60,000 individuals reveals diagnostic, prognostic and predictive imageable genes for a wide variety of major human diseases. Having both the critical size and focus to be altered in its expression during the development and progression of any human disease, the Imageable Genome will generate new imaging tools that improve the understanding, diagnosis and management of human diseases.
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Affiliation(s)
- Pablo Jané
- University of Geneva, Geneva, Switzerland
- Nuclear Medicine and Molecular Imaging Division, Geneva University Hospitals, Geneva, Switzerland
| | | | | | - Eduardo Jané
- Departamento de Matemática Aplicada a la Ingeniería Aeroespacial - ETSIAE, Universidad Politécnica de Madrid, 28040, Madrid, Spain
| | - Karim Gariani
- Division of Endocrinology, Diabetes, Nutrition and Patient Therapeutic Education, Geneva University Hospitals, Geneva, Switzerland
| | | | | | | | - María Del Val Gomez
- Servicio de Medicina Nuclear, Hospital Universitario Ramón y Cajal, Madrid, Spain
| | - Martin A Walter
- University of Lucerne, Lucerne, Switzerland.
- St. Anna Hospital, University of Lucerne, Lucerne, Switzerland.
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7
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Yang KC, Chou YH. Molecular imaging findings for treatment resistant depression. PROGRESS IN BRAIN RESEARCH 2023; 278:79-116. [PMID: 37414495 DOI: 10.1016/bs.pbr.2023.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/08/2023]
Abstract
Approximately 40% of patients with major depressive disorder (MDD) had limited response to conventional antidepressant treatments, resulting in treatment-resistant depression (TRD), a debilitating subtype that yielded a significant disease burden worldwide. Molecular imaging techniques, such as positron emission tomography (PET) and single photon emission tomography (SPECT), can measure targeted macromolecules or biological processes in vivo. These imaging tools provide a unique possibility to explore the pathophysiology and treatment mechanisms underlying TRD. This work reviewed and summarized prior PET and SPECT studies to examine the neurobiology and treatment-induced changes of TRD. A total of 51 articles were included with supplementary information from studies for MDD and healthy controls (HC). We found that there were altered regional blood flow or metabolic activity in several brain regions, such as the anterior cingulate cortex, prefrontal cortex, insula, hippocampus, amygdala, parahippocampus, and striatum. These regions have been suggested to engage in the pathophysiology or treatment resistance of depression. There was also limited data to demonstrate the changes in the markers of serotonin, dopamine, amyloid, and microglia over some regions in TRD. Moreover, several observed abnormal imaging indices were linked to treatment outcomes, supporting their specificity and clinical relevance. To address the limitations of the included studies, we proposed that future studies needed longitudinal designs, multimodal approaches, and radioligands targeting specific neural substrates for TRD to evaluate their baseline and treatment-related alterations in TRD. Adequate data sharing and reproducible data analysis can facilitate advances in this field.
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Affiliation(s)
- Kai-Chun Yang
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
| | - Yuan-Hwa Chou
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Center for Quality Management, Taipei Veterans General Hospital, Taipei, Taiwan
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