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Thurston LT, Skorska MN, Lobaugh NJ, Zucker KJ, Chakravarty MM, Lai MC, Chavez S, VanderLaan DP. White matter microstructure in transmasculine and cisgender adolescents: A multiparametric and multivariate study. PLoS One 2024; 19:e0300139. [PMID: 38470896 DOI: 10.1371/journal.pone.0300139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 02/21/2024] [Indexed: 03/14/2024] Open
Abstract
Adolescence is a sensitive developmental period for neural sex/gender differentiation. The present study used multiparametric mapping to better characterize adolescent white matter (WM) microstructure. WM microstructure was investigated using diffusion tensor indices (fractional anisotropy; mean, radial, and axial diffusivity [AD]) and quantitative T1 relaxometry (T1) in hormone therapy naïve adolescent cisgender girls, cisgender boys, and transgender boys (i.e., assigned female at birth and diagnosed with gender dysphoria). Diffusion indices were first analyzed for group differences using tract-based spatial statistics, which revealed a group difference in AD. Thus, two multiparametric and multivariate analyses assessed AD in conjunction with T1 relaxation time, and with respect to developmental proxy variables (i.e., age, serum estradiol, pubertal development, sexual attraction) thought to be relevant to adolescent brain development. The multivariate analyses showed a shared pattern between AD and T1 such that higher AD was associated with longer T1, and AD and T1 strongly related to all five developmental variables in cisgender boys (10 significant correlations, r range: 0.21-0.73). There were fewer significant correlations between the brain and developmental variables in cisgender girls (three correlations, r range: -0.54-0.54) and transgender boys (two correlations, r range: -0.59-0.77). Specifically, AD related to direction of sexual attraction (i.e., gynephilia, androphilia) in all groups, and T1 related to estradiol inversely in cisgender boys compared with transgender boys. These brain patterns may be indicative of less myelination and tissue density in cisgender boys, which corroborates other reports of protracted WM development in cisgender boys. Further, these findings highlight the importance of considering developmental trajectory when assessing the subtleties of neural structure associated with variations in sex, gender, and sexual attraction.
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Affiliation(s)
- Lindsey T Thurston
- Department of Psychology, University of Toronto Mississauga, Mississauga, Ontario, Canada
| | - Malvina N Skorska
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Nancy J Lobaugh
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Division of Neurology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Kenneth J Zucker
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Ontario, Canada
| | - Meng-Chuan Lai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, The Hospital for Sick Children, Toronto, Ontario, Canada
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Sofia Chavez
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Doug P VanderLaan
- Department of Psychology, University of Toronto Mississauga, Mississauga, Ontario, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
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Carlucci M, Lett T, Chavez S, Malinowski A, Lobaugh NJ, Petronis A. Diurnal oscillations of MRI metrics in the brains of male participants. Nat Commun 2023; 14:7044. [PMID: 37923728 PMCID: PMC10624685 DOI: 10.1038/s41467-023-42588-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 10/16/2023] [Indexed: 11/06/2023] Open
Abstract
Regulation of biological processes according to a 24-hr rhythm is essential for the normal functioning of an organism. Temporal variation in brain MRI data has often been attributed to circadian or diurnal oscillations; however, it is not clear if such oscillations exist. Here, we provide evidence that diurnal oscillations indeed govern multiple MRI metrics. We recorded cerebral blood flow, diffusion-tensor metrics, T1 relaxation, and cortical structural features every three hours over a 24-hr period in each of 16 adult male controls and eight adult male participants with bipolar disorder. Diurnal oscillations are detected in numerous MRI metrics at the whole-brain level, and regionally. Rhythmicity parameters in the participants with bipolar disorder are similar to the controls for most metrics, except for a larger phase variation in cerebral blood flow. The ubiquitous nature of diurnal oscillations has broad implications for neuroimaging studies and furthers our understanding of the dynamic nature of the human brain.
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Affiliation(s)
- Matthew Carlucci
- The Krembil Family Epigenetics Laboratory, The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, M5T 1R8, ON, Canada
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, LT-10257, Lithuania
| | - Tristram Lett
- Center for Population Neuroscience and Precision Medicine (PONS), Clinic for Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, 10117, Germany
| | - Sofia Chavez
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Alexandra Malinowski
- The Krembil Family Epigenetics Laboratory, The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, M5T 1R8, ON, Canada
| | - Nancy J Lobaugh
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Art Petronis
- The Krembil Family Epigenetics Laboratory, The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, M5T 1R8, ON, Canada.
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, LT-10257, Lithuania.
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
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Watling SE, Rhind SG, Warsh J, Green D, McCluskey T, Tong J, Truong P, Chavez S, Richardson JD, Kish SJ, Boileau I. Exploring brain glutathione and peripheral blood markers in posttraumatic stress disorder: a combined [1H]MRS and peripheral blood study. Front Psychiatry 2023; 14:1195012. [PMID: 37333909 PMCID: PMC10272391 DOI: 10.3389/fpsyt.2023.1195012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 05/09/2023] [Indexed: 06/20/2023] Open
Abstract
Introduction Oxidative stress has been implicated in psychiatric disorders, including posttraumatic stress disorder (PTSD). Currently, the status of glutathione (GSH), the brain's most abundant antioxidant, in PTSD remains uncertain. Therefore, the current study investigated brain concentrations of GSH and peripheral concentrations of blood markers in individuals with PTSD vs. Healthy Controls (HC). Methods GSH spectra was acquired in the anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (DLPFC) using MEGA-PRESS, a J-difference-editing acquisition method. Peripheral blood samples were analyzed for concentrations of metalloproteinase (MMP)-9, tissue inhibitors of MMP (TIMP)-1,2, and myeloperoxidase (MPO). Results There was no difference in GSH between PTSD and HC in the ACC (n = 30 PTSD, n = 20 HC) or DLPFC (n = 14 PTSD, n = 18 HC). There were no group differences between peripheral blood markers (P > 0.3) except for (non-significantly) lower TIMP-2 in PTSD. Additionally, TIMP-2 and GSH in the ACC were positively related in those with PTSD. Finally, MPO and MMP-9 were negatively associated with duration of PTSD. Conclusions We do not report altered GSH concentrations in the ACC or DLPFC in PTSD, however, systemic MMPs and MPO might be implicated in central processes and progression of PTSD. Future research should investigate these relationships in larger sample sizes.
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Affiliation(s)
- Sarah E. Watling
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Shawn G. Rhind
- Faculty of Kinesiology & Physical Education, University of Toronto, Toronto, ON, Canada
- Defence Research and Development Canada, Toronto Research Centre, Toronto, ON, Canada
| | - Jerry Warsh
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - Duncan Green
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tina McCluskey
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Junchao Tong
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Peter Truong
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Sofia Chavez
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - J. Don Richardson
- The MacDonald Franklin Operational Stress Injury (OSI) Research Centre, Lawson Health Research Institute, London, ON, Canada
- Department of Psychiatry, Western University, London, ON, Canada
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
- St. Joseph's London Operational Stress Injury (OSI), Parkwood Institute, St. Joseph's Health Care, London, ON, Canada
| | - Stephen J. Kish
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - Isabelle Boileau
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
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Cucalon M, Quijije C, Chavez S. Risk Assessment Of Eating Disorders In University Population. Clin Nutr ESPEN 2023. [DOI: 10.1016/j.clnesp.2022.09.204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2023]
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Watling SE, Jagasar S, McCluskey T, Warsh J, Rhind SG, Truong P, Chavez S, Houle S, Tong J, Kish SJ, Boileau I. Imaging oxidative stress in brains of chronic methamphetamine users: A combined 1H-magnetic resonance spectroscopy and peripheral blood biomarker study. Front Psychiatry 2023; 13:1070456. [PMID: 36704729 PMCID: PMC9871559 DOI: 10.3389/fpsyt.2022.1070456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 12/20/2022] [Indexed: 01/13/2023] Open
Abstract
Introduction Preclinical data suggest methamphetamine (MA), a widely used stimulant drug, can harm the brain by causing oxidative stress and inflammation, but only limited information is available in humans. We tested the hypothesis that levels of glutathione (GSH), a major antioxidant, would be lower in the brains of chronic human MA preferring polysubstance users. We also explored if concentrations of peripheral immunoinflammatory blood biomarkers were related with brain GSH concentrations. Methods 20 healthy controls (HC) (33 years; 11 M) and 14 MA users (40 years; 9 M) completed a magnetic resonance spectroscopy (MRS) scan, with GSH spectra obtained by the interleaved J-difference editing MEGA-PRESS method in anterior cingulate cortex (ACC) and left dorsolateral prefrontal cortex (DLPFC). Peripheral blood samples were drawn for measurements of immunoinflammatory biomarkers. Independent samples t-tests evaluated MA vs. HC differences in GSH. Results GSH levels did not differ between HC and MA users (ACC p = 0.30; DLPFC p = 0.85). A total of 17 of 25 immunoinflammatory biomarkers were significantly elevated in MA users and matrix metalloproteinase (MMP)-2 (r = 0.577, p = 0.039), myeloperoxidase (MPO) (r = -0.556, p = 0.049), and MMP-9 (r = 0.660, p = 0.038) were correlated with brain levels of GSH. Conclusion Normal brain GSH in living brain of chronic MA users is consistent with our previous postmortem brain finding and suggests that any oxidative stress caused by MA, at the doses used by our participants, might not be sufficient to cause either a compensatory increase in, or substantial overutilization of, this antioxidant. Additionally, more research is required to understand how oxidative stress and inflammatory processes are related and potentially dysregulated in MA use.
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Affiliation(s)
- Sarah E. Watling
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Samantha Jagasar
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tina McCluskey
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Jerry Warsh
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - Shawn G. Rhind
- Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, Canada
- Defence Research and Development Canada, Toronto Research Centre, Toronto, ON, Canada
| | - Peter Truong
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Sofia Chavez
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Sylvain Houle
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Junchao Tong
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Stephen J. Kish
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - Isabelle Boileau
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Campbell Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
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6
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Grández J, Oliva M, Morales E, Goñas M, Chavez S, Guivin A, Quiñones L, Milla M. Evaluation of Heavy Metals in Vegetables from Two Origins Marketed in Northern Peru. Nat Env Poll Tech 2022. [DOI: 10.46488/nept.2022.v21i05.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
The objective of the study was to evaluate the concentration of arsenic, chromium, cadmium, and lead in onion (Allium fistulosum and Allium cepa), tomato (Solanum lycopersicum), and celery (Apium graveolens) from two origins (local - Chachapoyas province and from the coast-province of Chiclayo) that are sold in the model market of the city of Chachapoyas. Six samples were taken on three different dates in November 2020, which were collected by non-probabilistic sampling (by convenience), which allowed choosing the most appropriate sample (according to its origin). For the determination of heavy metals, the Agilent 4100 MP-AES spectrometer was used. The concentration of As, Cr, and Cd in the vegetables remained below the Maximum Allowable Limits of the international standards with which they were compared; however, the concentration of Pb exceeded the Maximum Allowable Limits in all the samples analyzed, obtaining the lowest value in the celery samples from the local origin (0.15 mg.kg-1) and the highest value in the tomato samples from the coast (0.21 mg.kg-1). Therefore, it is concluded that only Pb is higher than the Maximum Allowable Limits with which it was compared.
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Watts JJ, Guma E, Chavez S, Tyndale RF, Ross RA, Houle S, Wilson AA, Chakravarty M, Rusjan PM, Mizrahi R. In vivo brain endocannabinoid metabolism is related to hippocampus glutamate and structure - a multimodal imaging study with PET, 1H-MRS, and MRI. Neuropsychopharmacology 2022; 47:1984-1991. [PMID: 35906490 PMCID: PMC9485131 DOI: 10.1038/s41386-022-01384-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 06/17/2022] [Accepted: 07/07/2022] [Indexed: 01/18/2023]
Abstract
Dysregulation of hippocampus glutamatergic neurotransmission and reductions in hippocampal volume have been associated with psychiatric disorders. The endocannabinoid system modulates glutamate neurotransmission and brain development, including hippocampal remodeling. In humans, elevated levels of anandamide and lower activity of its catabolic enzyme fatty acid amide hydrolase (FAAH) are associated with schizophrenia diagnosis and psychotic symptom severity, respectively (Neuropsychopharmacol, 29(11), 2108-2114; Biol. Psychiatry 88 (9), 727-735). Although preclinical studies provide strong evidence linking anandamide and FAAH to hippocampus neurotransmission and structure, these relationships remain poorly understood in humans. We recruited young adults with and without psychotic disorders and measured FAAH activity, hippocampal glutamate and glutamine (Glx), and hippocampal volume using [11C]CURB positron emission tomography (PET), proton magnetic resonance spectroscopy (1H-MRS) and T1-weighted structural MRI, respectively. We hypothesized that higher FAAH activity would be associated with greater hippocampus Glx and lower hippocampus volume, and that these effects would differ in patients with psychotic disorders relative to healthy control participants. After attrition and quality control, a total of 37 participants (62% male) completed [11C]CURB PET and 1H-MRS of the left hippocampus, and 45 (69% male) completed [11C]CURB PET and hippocampal volumetry. Higher FAAH activity was associated with greater concentration of hippocampal Glx (F1,36.36 = 9.17, p = 0.0045; Cohen's f = 0.30, medium effect size) and smaller hippocampal volume (F1,44.70 = 5.94, p = 0.019, Cohen's f = 0.26, medium effect size). These effects did not differ between psychosis and healthy control groups (no group interaction). This multimodal imaging study provides the first in vivo evidence linking hippocampal Glx and hippocampus volume with endocannabinoid metabolism in the human brain.
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Affiliation(s)
- Jeremy J Watts
- Research Centre, CHU Sainte-Justine, Montreal, QC, Canada
- Department of Psychiatry, Université de Montréal, Montreal, QC, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Elisa Guma
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, QC, Canada
- Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Sofia Chavez
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Rachel F Tyndale
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Ruth A Ross
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Sylvain Houle
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Alan A Wilson
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Mallar Chakravarty
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Pablo M Rusjan
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Romina Mizrahi
- Department of Psychiatry, McGill University, Montreal, QC, Canada.
- Douglas Mental Health University Institute, Montreal, QC, Canada.
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Skorska MN, Lobaugh NJ, Lombardo MV, van Bruggen N, Chavez S, Thurston LT, Aitken M, Zucker KJ, Chakravarty MM, Lai MC, VanderLaan DP. Inter-Network Brain Functional Connectivity in Adolescents Assigned Female at Birth Who Experience Gender Dysphoria. Front Endocrinol (Lausanne) 2022; 13:903058. [PMID: 35937791 PMCID: PMC9353716 DOI: 10.3389/fendo.2022.903058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 06/15/2022] [Indexed: 11/13/2022] Open
Abstract
Gender dysphoria (GD) is characterized by distress due to an incongruence between experienced gender and sex assigned at birth. Brain functional connectivity in adolescents who experience GD may be associated with experienced gender (vs. assigned sex) and/or brain networks implicated in own-body perception. Furthermore, sexual orientation may be related to brain functional organization given commonalities in developmental mechanisms proposed to underpin GD and same-sex attractions. Here, we applied group independent component analysis to resting-state functional magnetic resonance imaging (rs-fMRI) BOLD timeseries data to estimate inter-network (i.e., between independent components) timeseries correlations, representing functional connectivity, in 17 GD adolescents assigned female at birth (AFAB) not receiving gender-affirming hormone therapy, 17 cisgender girls, and 15 cisgender boys (ages 12-17 years). Sexual orientation was represented by degree of androphilia-gynephilia and sexual attractions strength. Multivariate partial least squares analyses found that functional connectivity differed among cisgender boys, cisgender girls, and GD AFAB, with the largest difference between cisgender boys and GD AFAB. Regarding sexual orientation and age, the brain's intrinsic functional organization of GD AFAB was both similar to and different from cisgender girls, and both differed from cisgender boys. The pattern of group differences and the networks involved aligned with the hypothesis that brain functional organization is different among GD AFAB (vs. cisgender) adolescents, and certain aspects of this organization relate to brain areas implicated in own-body perception and self-referential thinking. Overall, brain functional organization of GD AFAB was generally more similar to that of cisgender girls than cisgender boys.
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Affiliation(s)
- Malvina N. Skorska
- Child and Youth Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Nancy J. Lobaugh
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Michael V. Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Nina van Bruggen
- Department of Psychology, University of Toronto Mississauga, Mississauga, ON, Canada
| | - Sofia Chavez
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Lindsey T. Thurston
- Department of Psychology, University of Toronto Mississauga, Mississauga, ON, Canada
| | - Madison Aitken
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Kenneth J. Zucker
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - M. Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, PQ, Canada
- Department of Psychiatry, McGill University, Montreal, PQ, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, PQ, Canada
| | - Meng-Chuan Lai
- Child and Youth Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- The Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry and Autism Research Unit, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Doug P. VanderLaan
- Child and Youth Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychology, University of Toronto Mississauga, Mississauga, ON, Canada
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Shyu C, Chavez S, Boileau I, Foll BL. Quantifying GABA in Addiction: A Review of Proton Magnetic Resonance Spectroscopy Studies. Brain Sci 2022; 12:brainsci12070918. [PMID: 35884725 PMCID: PMC9316447 DOI: 10.3390/brainsci12070918] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 07/07/2022] [Accepted: 07/09/2022] [Indexed: 02/04/2023] Open
Abstract
Gamma-aminobutyric acid (GABA) signaling plays a crucial role in drug reward and the development of addiction. Historically, GABA neurochemistry in humans has been difficult to study due to methodological limitations. In recent years, proton magnetic resonance spectroscopy (1H-MRS, MRS) has emerged as a non-invasive imaging technique that can detect and quantify human brain metabolites in vivo. Novel sequencing and spectral editing methods have since been developed to allow for quantification of GABA. This review outlines the clinical research utilization of 1H-MRS in understanding GABA neurochemistry in addiction and summarizes current literature that reports GABA measurements by MRS in addiction. Research on alcohol, nicotine, cocaine, and cannabis addiction all suggest medications that modulate GABA signaling may be effective in reducing withdrawal, craving, and other addictive behaviors. Thus, we discuss how improvements in current MRS techniques and design can optimize GABA quantification in future studies and explore how monitoring changes to brain GABA could help identify risk factors, improve treatment efficacy, further characterize the nature of addiction, and provide crucial insights for future pharmacological development.
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Affiliation(s)
- Claire Shyu
- Translational Addiction Research Laboratory, Centre for Addiction and Mental Health, Toronto, ON M5S 2S1, Canada;
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada; (S.C.); (I.B.)
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Sofia Chavez
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada; (S.C.); (I.B.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, Division of Brain and Therapeutics, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Isabelle Boileau
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada; (S.C.); (I.B.)
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, Division of Brain and Therapeutics, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Bernard Le Foll
- Translational Addiction Research Laboratory, Centre for Addiction and Mental Health, Toronto, ON M5S 2S1, Canada;
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada; (S.C.); (I.B.)
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
- Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, Division of Brain and Therapeutics, University of Toronto, Toronto, ON M5T 1R8, Canada
- Centre for Addiction and Mental Health, Concurrent Outpatient Medical & Psychosocial Addiction Support Services, Toronto, ON M6J 1H4, Canada
- Centre for Addiction and Mental Health, Acute Care Program, Toronto, ON M6J 1H3, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, ON M5G 1V7, Canada
- Waypoint Centre for Mental Health Care, Waypoint Research Institute, 500 Church Street, Penetanguishene, ON L9M 1G3, Canada
- Correspondence: ; Tel.: +1-416-535-8501
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10
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Metcalf ES, Battaglia D, Chavez S, Ferris R, O'Leary T. Developmental Competence of equine MI oocytes following in vitro maturation culture. J Equine Vet Sci 2022. [DOI: 10.1016/j.jevs.2022.103962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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11
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Elsaid S, Rubin-Kahana DS, Kloiber S, Kennedy SH, Chavez S, Le Foll B. Neurochemical Alterations in Social Anxiety Disorder (SAD): A Systematic Review of Proton Magnetic Resonance Spectroscopic Studies. Int J Mol Sci 2022; 23:ijms23094754. [PMID: 35563145 PMCID: PMC9105768 DOI: 10.3390/ijms23094754] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/18/2022] [Accepted: 04/18/2022] [Indexed: 12/10/2022] Open
Abstract
(1) Objective: Considering that current knowledge of mechanisms involved in the molecular pathogenesis of Social Anxiety Disorder (SAD) is limited, we conducted a systematic review to evaluate cumulative data obtained by Proton Magnetic Resonance Spectroscopic (1H MRS) studies. (2) Methods: A computer-based literature search of Medline, EMBASE, PsycInfo, and ProQuest was performed. Only cross-sectional studies using 1H MRS techniques in participants with SAD and healthy controls (HCs) were selected. (3) Results: The search generated eight studies. The results indicated regional abnormalities in the ‘fear neurocircuitry’ in patients with SAD. The implicated regions included the anterior cingulate cortex (ACC), dorsomedial prefrontal cortex (dmPFC), dorsolateral prefrontal cortex (dlPFC), insula, occipital cortex (OC), as well as the subcortical regions, including the thalamus, caudate, and the putamen. (4) Conclusions: The evidence derived from eight studies suggests that possible pathophysiological mechanisms of SAD include impairments in the integrity and function of neurons and glial cells, including disturbances in energy metabolism, maintenance of phospholipid membranes, dysregulations of second messenger systems, and excitatory/inhibitory neurocircuitry. Conducting more cross-sectional studies with larger sample sizes is warranted given the limited evidence in this area of research.
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Affiliation(s)
- Sonja Elsaid
- Translational Addiction Research Laboratory, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5S 2S1, Canada; (S.E.); (D.S.R.-K.)
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada; (S.K.); (S.H.K.); (S.C.)
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
| | - Dafna S. Rubin-Kahana
- Translational Addiction Research Laboratory, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5S 2S1, Canada; (S.E.); (D.S.R.-K.)
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Stefan Kloiber
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada; (S.K.); (S.H.K.); (S.C.)
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
- Department of Pharmacology and Toxicology, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Sidney H. Kennedy
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada; (S.K.); (S.H.K.); (S.C.)
- Centre for Depression and Suicide Studies, Unity Health Toronto, Toronto, ON M5B 1M4, Canada
- Li Ka Shing Knowledge Institute, Toronto, ON M5B 1T8, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
- Homewood Research Institute, Guelph, ON N1E 6K9, Canada
| | - Sofia Chavez
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada; (S.K.); (S.H.K.); (S.C.)
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
| | - Bernard Le Foll
- Translational Addiction Research Laboratory, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5S 2S1, Canada; (S.E.); (D.S.R.-K.)
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada; (S.K.); (S.H.K.); (S.C.)
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
- Department of Pharmacology and Toxicology, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
- Departments of Family and Community Medicine, University of Toronto, Toronto, ON M5T 1R8, Canada
- Addictions Division, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada
- Waypoint Research Institute, Waypoint Centre for Mental Health Care, Penetanguishene, ON L9M 1G3, Canada
- Correspondence: ; Tel.: +1-416-535-8501 (ext. 33111)
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12
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Martin L, Saha S, Linton L, Taylor M, Zhu J, Chavez S, Stanisz G, Minkin S, Boyd N. Dietary Fiber, Insulin and Breast Tissue Composition at Age 15-18: A Cross-Sectional Study. Nutr Cancer 2022; 74:2946-2954. [PMID: 35243935 DOI: 10.1080/01635581.2022.2047738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND Risk of breast cancer in adult life is influenced by body size and height in childhood, but the mechanisms responsible for these associations are currently unknown. We carried out research to determine if, at age 15-18, measures of dietary intake were associated with body size, hormones, and with variations in breast tissue composition that in adult life are associated with risk of breast cancer. METHODS In a cross-sectional study of 766 healthy Caucasian women aged 15-18, we measured percent breast water (PBW), total breast water and fat by magnetic resonance (MR), and assessed dietary intake using a validated food frequency questionnaire. We also measured height, weight, skin-fold thicknesses and waist-to-hip ratio, and in fasting blood assayed glucose and insulin. RESULTS After adjustment for age, measures of body size, and energy intake, dietary fiber (insoluble and total fiber) and insulin were associated positively and significantly with PBW. CONCLUSIONS Dietary fiber and fasting insulin were associated with breast tissue measures. These data suggest a potential approach to breast cancer prevention.
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Affiliation(s)
- Lisa Martin
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Sudipta Saha
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Linda Linton
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Monica Taylor
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Jie Zhu
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Sofia Chavez
- Imaging Research, Sunnybrook Hospital, Toronto, ON, Canada
| | - Greg Stanisz
- Imaging Research, Sunnybrook Hospital, Toronto, ON, Canada
| | - Salomon Minkin
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Norman Boyd
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
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13
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Shyu C, Elsaid S, Truong P, Chavez S, Le Foll B. MR Spectroscopy of the Insula: Within- and between-Session Reproducibility of MEGA-PRESS Measurements of GABA+ and Other Metabolites. Brain Sci 2021; 11:brainsci11111538. [PMID: 34827537 PMCID: PMC8615582 DOI: 10.3390/brainsci11111538] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 11/01/2021] [Accepted: 11/12/2021] [Indexed: 11/25/2022] Open
Abstract
The insula plays a critical role in many neuropsychological disorders. Research investigating its neurochemistry with magnetic resonance spectroscopy (MRS) has been limited compared with cortical regions. Here, we investigate the within-session and between-session reproducibility of metabolite measurements in the insula on a 3T scanner. We measure N-acetylaspartate + N-acetylaspartylglutamate (tNAA), creatine + phosphocreatine (tCr), glycerophosphocholine + phosphocholine (tCho), myo-inositol (Ins), glutamate + glutamine (Glx), and γ-aminobutyric acid (GABA) in one cohort using a j-edited MEGA-PRESS sequence. We measure tNAA, tCr, tCho, Ins, and Glx in another cohort with a standard short-TE PRESS sequence as a reference for the reproducibility metrics. All participants were scanned 4 times identically: 2 back-to-back scans each day, on 2 days. Preprocessing was done using LCModel and Gannet. Reproducibility was determined using Pearson’s r, intraclass-correlation coefficients (ICC), coefficients of variation (CV%), and Bland–Altman plots. A MEGA-PRESS protocol requiring averaged results over two 6:45-min scans yielded reproducible GABA measurements (CV% = 7.15%). This averaging also yielded reproducibility metrics comparable to those from PRESS for the other metabolites. Voxel placement inconsistencies did not affect reproducibility, and no sex differences were found. The data suggest that MEGA-PRESS can reliably measure standard metabolites and GABA in the insula.
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Affiliation(s)
- Claire Shyu
- Translational Addiction Research Laboratory, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON M5S 2S1, Canada; (C.S.); (S.E.)
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada; (P.T.); (S.C.)
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Sonja Elsaid
- Translational Addiction Research Laboratory, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON M5S 2S1, Canada; (C.S.); (S.E.)
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada; (P.T.); (S.C.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Peter Truong
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada; (P.T.); (S.C.)
| | - Sofia Chavez
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada; (P.T.); (S.C.)
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, Division of Brain and Therapeutics, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Bernard Le Foll
- Translational Addiction Research Laboratory, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON M5S 2S1, Canada; (C.S.); (S.E.)
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON M5S 1A8, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, Division of Brain and Therapeutics, University of Toronto, Toronto, ON M5T 1R8, Canada
- Concurrent Outpatient Medical & Psychosocial Addiction Support Services, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Acute Care Program, Centre for Addiction and Mental Health, Toronto, ON M6J 1H3, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, ON M5T 1R8, Canada
- Correspondence: ; Tel.: +1-416-535-8501
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14
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Iwata Y, Nakajima S, Plitman E, Truong P, Bani-Fatemi A, Caravaggio F, Kim J, Shah P, Mar W, Chavez S, Remington G, Gerretsen P, De Luca V, Sailasuta N, Graff-Guerrero A. Glutathione Levels and Glutathione-Glutamate Correlation in Patients With Treatment-Resistant Schizophrenia. ACTA ACUST UNITED AC 2021; 2:sgab006. [PMID: 33969302 PMCID: PMC8086698 DOI: 10.1093/schizbullopen/sgab006] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Treatment-resistant schizophrenia (TRS) has been suggested to involve glutamatergic dysfunction. Glutathione (GSH), a dominant antioxidant, is known to be involved in glutamatergic neurotransmission. To date, no study has examined GSH levels in patients with TRS. The aim of this study was to examine GSH levels in the dorsal anterior cingulate cortex (dACC) of patients with TRS. Patients with schizophrenia were categorized into 3 groups with respect to their antipsychotic response: (1) clozapine (CLZ) nonresponders, (2) CLZ responders, and (3) first-line responders (FLR). GSH and glutamine + glutamate (Glx) levels were measured using 3T proton magnetic resonance spectroscopy. Firstly, dACC GSH levels were compared among the patient groups and healthy controls (HCs). Further, relationships between GSH and Glx levels were compared between the groups and GSH levels were explored stratifying the patient groups based on the glutamate-cysteine ligase catalytic (GCLC) subunit polymorphism. There was no difference in GSH levels between the groups. FLR showed a more negative relationship between GSH and Glx levels in the dACC compared to HCs. There were no effects of GCLC genotype on the GSH levels. However, CLZ responders had a higher ratio of high-risk GCLC genotype compared to CLZ nonresponders. This study demonstrated different relationships between GSH and Glx in the dACC between groups. In addition, the results suggest a potential link between CLZ response and GCLC genotype. However, it still remains unclear how these differences are related to the underlying pathophysiology of schizophrenia subtypes or the mechanisms of action of CLZ.
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Affiliation(s)
- Yusuke Iwata
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Shinichiro Nakajima
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Eric Plitman
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Peter Truong
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Ali Bani-Fatemi
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Fernando Caravaggio
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Julia Kim
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Parita Shah
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Wanna Mar
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Sofia Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Gary Remington
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada.,Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Philip Gerretsen
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Vincenzo De Luca
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Napapon Sailasuta
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Department of Tropical Medicine, University of Hawaii, Honolulu, HI, USA
| | - Ariel Graff-Guerrero
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, ON, Canada
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15
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Criaud M, Kim JH, Zurowski M, Lobaugh N, Chavez S, Houle S, Strafella AP. Anxiety in Parkinson's disease: Abnormal resting activity and connectivity. Brain Res 2021; 1753:147235. [PMID: 33412150 DOI: 10.1016/j.brainres.2020.147235] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 11/19/2020] [Accepted: 12/07/2020] [Indexed: 11/25/2022]
Abstract
Anxiety is a very common yet poorly understood symptom of Parkinson's disease. We investigated whether Parkinson's disease patients experiencing anxiety share neural mechanisms described in the general population with involvement of critical regions for the control of behaviour and movement. Thirty-nine patients with PD were recruited for this study, 20 with higher anxiety scores and 19 with lower anxiety scores. They all underwent a resting-state fMRI scan, while they were on medication. The amplitude of low-frequency fluctuation (ALFF) and seed-based connectivity were investigated to reveal the changes of the spontaneous activity and the interaction among different related regions. The results provided evidence that anxiety in Parkinson's disease is associated with the over-activation of the amygdala and impaired inter-relationship of regions involved in behavior (i.e. medial prefrontal cortex, insula) and motor control (i.e. basal ganglia).
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Affiliation(s)
- Marion Criaud
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada; Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, UHN, University of Toronto, Ontario, Canada.
| | - Jin-Hee Kim
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada; Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, UHN, University of Toronto, Ontario, Canada
| | - Mateusz Zurowski
- Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, UHN, University of Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Ontario, Canada
| | - Nancy Lobaugh
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada; Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Sofia Chavez
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada
| | - Sylvain Houle
- Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada
| | - Antonio P Strafella
- Morton and Gloria Shulman Movement Disorder Unit & E.J. Safra Parkinson Disease Program, Toronto Western Hospital, UHN, University of Toronto, Ontario, Canada; Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada; Division of Brain, Imaging and Behaviour - Systems Neuroscience, Krembil Research Institute, UHN, University of Toronto, Ontario, Canada; Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada.
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16
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Desmond KL, Xu R, Sun Y, Chavez S. A practical method for post-acquisition reduction of bias in fast, whole-brain B1-maps. Magn Reson Imaging 2020; 77:88-98. [PMID: 33338561 DOI: 10.1016/j.mri.2020.12.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 11/22/2020] [Accepted: 12/13/2020] [Indexed: 12/24/2022]
Abstract
Large consistent differences have been observed between maps of the flip angle correction factor (commonly called "B1-maps") produced with different fast methods in the human brain. We present an empirical procedure for first-order multiplicative bias correction that can be applied when more than one B1-mapping method is available. We use a B1-map measurement in a calibration phantom as a reference and the voxel-wise histogram mode between ratios of B1-maps produced from different methods to calculate determine the bias as a multiplicative correcting scale factor. Institutional implementations of four common methods of B1-mapping were assessed: Method of Slopes, FSE and EPI double angle methods (DAM), and Bloch-Siegert. In human subjects, the multiplicative bias used to correct for each of the four methods was: Method of Slopes = 1.005, FSE-DAM = 0.956, EPI-DAM = 1.080, and Bloch-Siegert = 1.128. Scaling to remove this bias between methods produces more consistent B1-maps which enable more consistent values for any computations requiring flip angle correction. In addition, we present evidence that the corrected B1 maps, using our calibration method, are also more accurate.
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Affiliation(s)
- Kimberly L Desmond
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario M5T 1R8, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario M5T 1R8, Canada.
| | - Ruiyang Xu
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario M5T 1R8, Canada
| | - Yutong Sun
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario M5T 1R8, Canada
| | - Sofia Chavez
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario M5T 1R8, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario M5T 1R8, Canada
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17
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Chavez S, Galarraga J. 135 Effects of Maryland’s Health Enterprise Zones on Disparities in Emergency Department Returns. Ann Emerg Med 2020. [DOI: 10.1016/j.annemergmed.2020.09.146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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18
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Kim J, Plitman E, Iwata Y, Nakajima S, Mar W, Patel R, Chavez S, Chung JK, Caravaggio F, Chakravarty MM, Remington G, Gerretsen P, Graff-Guerrero A. Neuroanatomical profiles of treatment-resistance in patients with schizophrenia spectrum disorders. Prog Neuropsychopharmacol Biol Psychiatry 2020; 99:109839. [PMID: 31843627 DOI: 10.1016/j.pnpbp.2019.109839] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 11/10/2019] [Accepted: 12/12/2019] [Indexed: 01/18/2023]
Abstract
Widespread structrual abnormalities in subcortical brain regions have been identified in patients with schizophrenia. However, only a few studies have examined the neuroanatomical profiles of patients with treatment-resistant schizophrenia. The aim of this study was to compare differences in subcortical and hippocampal volumes between: (i) treatment-resistant patients who are non-responders to both first-line antipsychotics and clozapine (URS), (ii) treatment-resistant patients who are non-responders to first-line antipsychotics but are responders to clozapine (CLZ-Resp), (iii) responders to first-line antipsychotics (FL-Resp), and (iv) healthy controls. T1-weighted images of 103 participants (27 URS, 29 CLZ-Resp, 21 FL-Resp, and 26 healthy controls) were obtained. Group differences in striatal, thalamic, globus pallidus, amygdala, and hippocampus volumes were examined. Multiple regression analyses were performed to examine the associations between subcortical and hippocampal volumes and participant characteristics. The FL-Resp group showed larger striatal and globus pallidus volumes compared to the URS group and larger post-commissural putamen and globus pallidus volumes compared to healthy controls. The URS group showed smaller thalamic volume compared to healthy controls. There were no subcortical or hippocampal volume differences between the URS and CLZ-Resp groups. Differences in subcortical and hippocampal structural volumes were not related to symptom severity or chlorpromazine antipsychotic dose equivalents. Our findings suggest different structural volume alterations in subcortical brain regions between treatment-resistant schizophrenia and responders to first-line antipsychotics. Whether subcortical structure compromise is a distinct pathophysiological marker of treatment-resistant schizophrenia, or a result of antipsychotic exposure, remains to be explored.
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Affiliation(s)
- Julia Kim
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Eric Plitman
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Yusuke Iwata
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | | | - Wanna Mar
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Raihaan Patel
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Sofia Chavez
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Jun Ku Chung
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Fernando Caravaggio
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Gary Remington
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, Toronto, Ontario, Canada; Schizophrenia Division, CAMH, Toronto, Ontario, Canada
| | - Philip Gerretsen
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, CAMH, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, Toronto, Ontario, Canada
| | - Ariel Graff-Guerrero
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, CAMH, Toronto, Ontario, Canada; Campbell Family Mental Health Research Institute, CAMH, Toronto, Ontario, Canada.
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19
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Tarumi R, Tsugawa S, Noda Y, Plitman E, Honda S, Matsushita K, Chavez S, Sawada K, Wada M, Matsui M, Fujii S, Miyazaki T, Chakravarty MM, Uchida H, Remington G, Graff-Guerrero A, Mimura M, Nakajima S. Levels of glutamatergic neurometabolites in patients with severe treatment-resistant schizophrenia: a proton magnetic resonance spectroscopy study. Neuropsychopharmacology 2020; 45:632-640. [PMID: 31842203 PMCID: PMC7021829 DOI: 10.1038/s41386-019-0589-z] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 11/08/2019] [Accepted: 12/07/2019] [Indexed: 01/20/2023]
Abstract
Approximately 30% of patients with schizophrenia do not respond to antipsychotics and are thus considered to have treatment-resistant schizophrenia (TRS). To date, only four studies have examined glutamatergic neurometabolite levels using proton magnetic resonance spectroscopy (1H-MRS) in patients with TRS, collectively suggesting that glutamatergic dysfunction may be implicated in the pathophysiology of TRS. Notably, the TRS patient population in these studies had mild-to-moderate illness severity, which is not entirely reflective of what is observed in clinical practice. In this present work, we compared glutamate + glutamine (Glx) levels in the dorsal anterior cingulate cortex (dACC) and caudate among patients with TRS, patients with non-TRS, and healthy controls (HCs), using 3T 1H-MRS (PRESS, TE = 35 ms). TRS criteria were defined by severe positive symptoms (i.e., ≥5 on 2 Positive and Negative Syndrome Scale (PANSS)-positive symptom items or ≥4 on 3 PANSS-positive symptom items), despite standard antipsychotic treatment. A total of 95 participants were included (29 TRS patients [PANSS = 111.2 ± 20.4], 33 non-TRS patients [PANSS = 49.8 ± 13.7], and 33 HCs). dACC Glx levels were higher in the TRS group vs. HCs (group effect: F[2,75] = 4.74, p = 0.011; TRS vs. HCs: p = 0.012). No group differences were identified in the caudate. There were no associations between Glx levels and clinical severity in either patient group. Our results are suggestive of greater heterogeneity in TRS relative to non-TRS with respect to dACC Glx levels, necessitating further research to determine biological subtypes of TRS.
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Affiliation(s)
- Ryosuke Tarumi
- 0000 0004 1936 9959grid.26091.3cDepartment of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan ,grid.415439.eDepartment of Psychiatry, Komagino Hospital, Hachioji, Japan
| | - Sakiko Tsugawa
- 0000 0004 1936 9959grid.26091.3cDepartment of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Yoshihiro Noda
- 0000 0004 1936 9959grid.26091.3cDepartment of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Eric Plitman
- 0000 0004 1936 8649grid.14709.3bCerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC Canada ,0000 0004 1936 8649grid.14709.3bDepartment of Psychiatry, McGill University, Montreal, QC Canada
| | - Shiori Honda
- 0000 0004 1936 9959grid.26091.3cGraduate School of Media and Governance, Keio University, Tokyo, Japan
| | - Karin Matsushita
- 0000 0004 1936 9959grid.26091.3cFaculty of Environment and Information Studies, Keio University, Tokyo, Japan
| | - Sofia Chavez
- 0000 0000 8793 5925grid.155956.bCampbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, ON Canada
| | - Kyosuke Sawada
- 0000 0004 1936 9959grid.26091.3cDepartment of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Masataka Wada
- 0000 0004 1936 9959grid.26091.3cDepartment of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Mie Matsui
- 0000 0001 2308 3329grid.9707.9Department of Clinical Cognitive Neuroscience, Institute of Liberal Arts and Science, Kanazawa University, Kanazawa, Japan
| | - Shinya Fujii
- 0000 0004 1936 9959grid.26091.3cFaculty of Environment and Information Studies, Keio University, Tokyo, Japan
| | - Takahiro Miyazaki
- 0000 0004 1936 9959grid.26091.3cDepartment of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - M. Mallar Chakravarty
- 0000 0004 1936 8649grid.14709.3bCerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC Canada ,0000 0004 1936 8649grid.14709.3bDepartment of Psychiatry, McGill University, Montreal, QC Canada ,0000 0004 1936 8649grid.14709.3bDepartment of Biomedical Engineering, McGill University, Montreal, QC Canada
| | - Hiroyuki Uchida
- 0000 0004 1936 9959grid.26091.3cDepartment of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan ,0000 0000 8793 5925grid.155956.bCampbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, ON Canada
| | - Gary Remington
- 0000 0000 8793 5925grid.155956.bCampbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, ON Canada ,0000 0001 2157 2938grid.17063.33Department of Psychiatry, University of Toronto, Toronto, ON Canada
| | - Ariel Graff-Guerrero
- 0000 0000 8793 5925grid.155956.bCampbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, ON Canada ,0000 0001 2157 2938grid.17063.33Department of Psychiatry, University of Toronto, Toronto, ON Canada
| | - Masaru Mimura
- 0000 0004 1936 9959grid.26091.3cDepartment of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan. .,Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, ON, Canada.
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20
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Watts JJ, Garani R, Da Silva T, Lalang N, Chavez S, Mizrahi R. Evidence That Cannabis Exposure, Abuse, and Dependence Are Related to Glutamate Metabolism and Glial Function in the Anterior Cingulate Cortex: A 1H-Magnetic Resonance Spectroscopy Study. Front Psychiatry 2020; 11:764. [PMID: 32973572 PMCID: PMC7468488 DOI: 10.3389/fpsyt.2020.00764] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 07/20/2020] [Indexed: 02/06/2023] Open
Abstract
There is evidence that long-term cannabis use is associated with alterations to glutamate neurotransmission and glial function. In this study, 26 long-term cannabis users (males=65.4%) and 47 non-cannabis using healthy controls (males=44.6%) underwent proton magnetic resonance spectroscopy (1H-MRS) of the anterior cingulate cortex (ACC) in order to characterize neurometabolite alterations in cannabis users and to examine associations between neurometabolites, cannabis exposure, and cannabis use behaviors. Myo-inositol, a marker of glial function, and glutamate metabolites did not differ between healthy controls and cannabis users or cannabis users who met criteria for DSM5 cannabis use disorder (n=17). Lower myo-inositol, a putative marker of glial function, was related to greater problematic drug use (F1,22 = 11.95, p=.002; Cohen's f=0.59, large effect; Drug Abuse Screening Test) and severity of cannabis dependence (F1,22 = 6.61, p=.17; Cohen's f=0.44, large effect). Further, past-year cannabis exposure exerted different effects on glutamate and glutamate+glutamine in males and females (glutamate: F1,21 = 6.31, p=.02; glutamate+glutamine: F1,21 = 7.20, p=.014), such that greater past-year cannabis exposure was related to higher concentrations of glutamate metabolites in male cannabis users (glutamate: F1,14 = 25.94, p=.00016; Cohen's f=1.32, large effect; glutamate+glutamine: F1,14 = 23.24, p=.00027, Cohen's f=1.24, large effect) but not in female cannabis users (glutamate: F1,6 = 1.37, p=0.78; glutamate+glutamine: F1,6 = 0.001, p=.97). The present results extend existing evidence of altered glial function and glutamate metabolism with cannabis use by providing evidence linking problematic drug use behaviors with glial function as measured with myo-inositol and recent chronic cannabis exposure to alterations in glutamate metabolism. This provides novel directions for the interrogation of the impact of cannabis use on brain neurochemistry.
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Affiliation(s)
- Jeremy J Watts
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Ranjini Garani
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Tania Da Silva
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Nittha Lalang
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Sofia Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Romina Mizrahi
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
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21
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Smaragdi A, Chavez S, Lobaugh NJ, Meyer JH, Kolla NJ. Differential levels of prefrontal cortex glutamate+glutamine in adults with antisocial personality disorder and bipolar disorder: A proton magnetic resonance spectroscopy study. Prog Neuropsychopharmacol Biol Psychiatry 2019; 93:250-255. [PMID: 30959086 DOI: 10.1016/j.pnpbp.2019.04.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 03/20/2019] [Accepted: 04/03/2019] [Indexed: 02/06/2023]
Abstract
As the main excitatory neurotransmitter in the central nervous system, glutamate, as measured in combination with glutamine (Glx), is implicated in several psychopathologies when levels are aberrant. One illness that shows heightened Glx levels is bipolar disorder (BD), an illness characterized by high impulsivity. In addition, although animal studies have reported elevated levels of Glx in aggressive and impulsive phenotypes, no study, to our knowledge, has reported Glx in the human cortex in relation to aggression. Here, we addressed the question of whether elevated levels of Glx would be present in patients with BD and antisocial personality disorder (ASPD), a condition associated with aggression and, like BD, also presents high impulsivity. We recruited individuals with ASPD (n = 18), individuals with BD (n = 16), and a healthy control group (n = 24). We used proton magnetic resonance spectroscopy to measure relative neurometabolite concentrations in the left dorsolateral prefrontal cortex (dlPFC) and supra-genual anterior cingulate cortex (ACC), two brain regions associated with impulsivity and behavior control. We found significantly elevated levels of Glx in the ASPD group relative to the BD and healthy control groups in the dlPFC (p = .014), and a positive correlation between Glx levels and aggression in the dlPFC in the ASPD group alone (r = .59, p = .026). These findings suggest a link between aggression in ASPD and Glx levels.
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Affiliation(s)
- Areti Smaragdi
- Research Imaging Centre, Campbell Family Mental Health Research Institute, and Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Violence Prevention Neurobiological Research Unit, Forensic Psychiatry, CAMH, Toronto, ON, Canada; Child Development Institute, Toronto, ON, Canada
| | - Sofia Chavez
- Research Imaging Centre, Campbell Family Mental Health Research Institute, and Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Faculty of Medicine, Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Nancy J Lobaugh
- Research Imaging Centre, Campbell Family Mental Health Research Institute, and Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Faculty of Medicine, Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
| | - Jeffrey H Meyer
- Research Imaging Centre, Campbell Family Mental Health Research Institute, and Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Faculty of Medicine, Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Nathan J Kolla
- Research Imaging Centre, Campbell Family Mental Health Research Institute, and Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada; Violence Prevention Neurobiological Research Unit, Forensic Psychiatry, CAMH, Toronto, ON, Canada; Faculty of Medicine, Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Faculty of Arts and Science, Department of Criminology and Sociological Studies, University of Toronto, Toronto, ON, Canada; Waypoint Centre for Mental Health Care, Penetanguishene, ON, Canada.
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22
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Iwata Y, Nakajima S, Plitman E, Caravaggio F, Kim J, Shah P, Mar W, Chavez S, De Luca V, Mimura M, Remington G, Gerretsen P, Graff-Guerrero A. Glutamatergic Neurometabolite Levels in Patients With Ultra-Treatment-Resistant Schizophrenia: A Cross-Sectional 3T Proton Magnetic Resonance Spectroscopy Study. Biol Psychiatry 2019; 85:596-605. [PMID: 30389132 DOI: 10.1016/j.biopsych.2018.09.009] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 09/13/2018] [Accepted: 09/13/2018] [Indexed: 12/21/2022]
Abstract
BACKGROUND In terms of antipsychotic treatment response, patients with schizophrenia can be classified into three groups: 1) treatment resistant to both non-clozapine (non-CLZ) antipsychotics and CLZ (ultra-treatment-resistant schizophrenia [URS]), 2) treatment resistant to non-CLZ antipsychotics but CLZ-responsive schizophrenia [non-URS]), and 3) responsive to first-line antipsychotics (non-treatment-resistant schizophrenia). This study aimed to compare glutamatergic neurometabolite levels among these three patient groups and healthy control subjects using proton magnetic resonance spectroscopy. METHODS Glutamate and glutamate+glutamine levels were assessed in the caudate, the dorsal anterior cingulate cortex (dACC), and the dorsolateral prefrontal cortex using 3T proton magnetic resonance spectroscopy (point-resolved spectroscopy, echo time = 35 ms). Glutamatergic neurometabolite levels were compared between the groups. RESULTS A total of 100 participants were included, consisting of 26 patients with URS, 27 patients with non-URS, 21 patients with non-treatment-resistant schizophrenia, and 26 healthy control subjects. Group differences were detected in ACC glutamate+glutamine levels (F3,96 = 2.93, p = .038); patients with URS showed higher dACC glutamate+glutamine levels than healthy control subjects (p = .038). There were no group differences in the caudate or dorsolateral prefrontal cortex. CONCLUSIONS Taken together with previous studies that demonstrated higher ACC glutamate levels in patients with treatment-resistant schizophrenia, this study suggests that higher levels of ACC glutamatergic metabolites may be among the shared biological characteristics of treatment resistance to antipsychotics, including CLZ.
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Affiliation(s)
- Yusuke Iwata
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Shinichiro Nakajima
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Eric Plitman
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Fernando Caravaggio
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Julia Kim
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Parita Shah
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Wanna Mar
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Sofia Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Vincenzo De Luca
- Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Masaru Mimura
- Department of Neuropsychiatry, School of Medicine, Keio University, Tokyo, Japan
| | - Gary Remington
- Schizophrenia Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Philip Gerretsen
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Ariel Graff-Guerrero
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada.
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23
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Hawco C, Viviano JD, Chavez S, Dickie EW, Calarco N, Kochunov P, Argyelan M, Turner JA, Malhotra AK, Buchanan RW, Voineskos AN. A longitudinal human phantom reliability study of multi-center T1-weighted, DTI, and resting state fMRI data. Psychiatry Res Neuroimaging 2018; 282:134-142. [PMID: 29945740 PMCID: PMC6482446 DOI: 10.1016/j.pscychresns.2018.06.004] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 06/06/2018] [Accepted: 06/06/2018] [Indexed: 12/31/2022]
Abstract
Multi-center MRI studies can enhance power, generalizability, and discovery for clinical neuroimaging research in brain disorders. Here, we sought to establish the utility of a clustering algorithm as an alternative to more traditional intra-class correlation coefficient approaches in a longitudinal multi-center human phantom study. We completed annual reliability scans on 'travelling human phantoms'. Acquisitions across sites were harmonized prospectively. Twenty-seven MRI sessions were available across four participants, scanned on five scanners, across three years. For each scan, three metrics were extracted: cortical thickness (CT), white matter fractional anisotropy (FA), and resting state functional connectivity (FC). For each metric, hierarchical clustering (Ward's method) was performed. The cluster solutions were compared to participant and scanner using the adjusted Rand index (ARI). For all metrics, data clustered by participant rather than by scanner (ARI > 0.8 comparing clusters to participants, ARI < 0.2 comparing clusters to scanners). These results demonstrate that hierarchical clustering can reliably identify structural and functional scans from different participants imaged on different scanners across time. With increasing interest in data-driven approaches in psychiatric and neurologic brain imaging studies, our findings provide a framework for multi-center analytic approaches aiming to identify subgroups of participants based on brain structure or function.
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Affiliation(s)
- Colin Hawco
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Joseph D Viviano
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada
| | - Sofia Chavez
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Erin W Dickie
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada
| | - Navona Calarco
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada
| | - Peter Kochunov
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, P.O. Box 21247, Baltimore, MD, United States
| | - Miklos Argyelan
- Zucker Hillside Hospital, 75-59 263rd St, Glen Oaks, NY, United States
| | - Jessica A Turner
- Department of Psychology, Georgia State University, 33 Gilmer Street SE, Atlanta, GA, United States
| | - Anil K Malhotra
- Zucker Hillside Hospital, 75-59 263rd St, Glen Oaks, NY, United States; The Zucker School of Medicine at Hofstra/Northwell
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, P.O. Box 21247, Baltimore, MD, United States
| | - Aristotle N Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
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24
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Viviano JD, Buchanan RW, Calarco N, Gold JM, Foussias G, Bhagwat N, Stefanik L, Hawco C, DeRosse P, Argyelan M, Turner J, Chavez S, Kochunov P, Kingsley P, Zhou X, Malhotra AK, Voineskos AN. Resting-State Connectivity Biomarkers of Cognitive Performance and Social Function in Individuals With Schizophrenia Spectrum Disorder and Healthy Control Subjects. Biol Psychiatry 2018; 84:665-674. [PMID: 29779671 PMCID: PMC6177285 DOI: 10.1016/j.biopsych.2018.03.013] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 03/12/2018] [Accepted: 03/31/2018] [Indexed: 12/17/2022]
Abstract
BACKGROUND Deficits in neurocognition and social cognition are drivers of reduced functioning in schizophrenia spectrum disorders, with potentially shared neurobiological underpinnings. Many studies have sought to identify brain-based biomarkers of these clinical variables using a priori dichotomies (e.g., good vs. poor cognition, deficit vs. nondeficit syndrome). METHODS We evaluated a fully data-driven approach to do the same by building and validating a brain connectivity-based biomarker of social cognitive and neurocognitive performance in a sample using resting-state and task-based functional magnetic resonance imaging (n = 74 healthy control participants, n = 114 persons with schizophrenia spectrum disorder, 188 total). We used canonical correlation analysis followed by clustering to identify a functional connectivity signature of normal and poor social cognitive and neurocognitive performance. RESULTS Persons with poor social cognitive and neurocognitive performance were differentiated from those with normal performance by greater resting-state connectivity in the mirror neuron and mentalizing systems. We validated our findings by showing that poor performers also scored lower on functional outcome measures not included in the original analysis and by demonstrating neuroanatomical differences between the normal and poorly performing groups. We used a support vector machine classifier to demonstrate that functional connectivity alone is enough to distinguish normal and poorly performing participants, and we replicated our findings in an independent sample (n = 75). CONCLUSIONS A brief functional magnetic resonance imaging scan may ultimately be useful in future studies aimed at characterizing long-term illness trajectories and treatments that target specific brain circuitry in those with impaired cognition and function.
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Affiliation(s)
- Joseph D Viviano
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario
| | - Robert W Buchanan
- Department of Psychiatry, Maryland Psychiatric Research Center, Catonsville, Maryland
| | - Navona Calarco
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario
| | - James M Gold
- Department of Psychiatry, Maryland Psychiatric Research Center, Catonsville, Maryland
| | - George Foussias
- Department of Psychiatry, University of Toronto, Toronto, Ontario
| | - Nikhil Bhagwat
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario; Computational Brain Anatomy Laboratory, Brain Imaging Center, Douglas Mental Health University Institute, Verdun, Quebec, Canada
| | - Laura Stefanik
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario
| | - Colin Hawco
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario; Department of Psychiatry, University of Toronto, Toronto, Ontario
| | - Pamela DeRosse
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York
| | - Miklos Argyelan
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York
| | - Jessica Turner
- Department of Psychology, Georgia State University, Atlanta, Georgia
| | - Sofia Chavez
- Department of Psychiatry, University of Toronto, Toronto, Ontario; MRI Unit, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, Catonsville, Maryland
| | - Peter Kingsley
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York
| | - Xiangzhi Zhou
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York
| | - Anil K Malhotra
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hofstra University, Hempstead, Manhasset; Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, New York; Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, New York
| | - Aristotle N Voineskos
- Kimel Family Translational Imaging-Genetics Research Lab, Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario; Department of Psychiatry, University of Toronto, Toronto, Ontario.
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Shakory S, Watts JJ, Hafizi S, Da Silva T, Khan S, Kiang M, Bagby RM, Chavez S, Mizrahi R. Hippocampal glutamate metabolites and glial activation in clinical high risk and first episode psychosis. Neuropsychopharmacology 2018; 43:2249-2255. [PMID: 30087434 PMCID: PMC6135774 DOI: 10.1038/s41386-018-0163-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 07/17/2018] [Accepted: 07/19/2018] [Indexed: 02/06/2023]
Abstract
Alterations in glutamate neurotransmission have been implicated in the pathophysiology of schizophrenia, as well as in symptom severity and cognitive deficits. The hippocampus, in particular, is a site of key functional and structural abnormalities in schizophrenia. Yet few studies have investigated hippocampal glutamate in antipsychotic-naïve first episode psychosis patients or in individuals at clinical high risk (CHR) of developing psychosis. Using proton magnetic resonance spectroscopy (1H-MRS), we investigated glutamate metabolite levels in the left hippocampus of 25 CHR (19 antipsychotic-naïve), 16 patients with first-episode psychosis (13 antipsychotic-naïve) and 31 healthy volunteers. We also explored associations between hippocampal glutamate metabolites and glial activation, as indexed by [18F]FEPPA positron emission tomography (PET); symptom severity; and cognitive function. Groups differed significantly in glutamate plus glutamine (Glx) levels (F(2, 69) = 6.39, p = 0.003). Post-hoc analysis revealed that CHR had significantly lower Glx levels than both healthy volunteers (p = 0.003) and first-episode psychosis patients (p = 0.050). No associations were found between glutamate metabolites and glial activation. Our findings suggest that glutamate metabolites are altered in CHR.
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Affiliation(s)
- Shima Shakory
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jeremy J Watts
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - Sina Hafizi
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tania Da Silva
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Saad Khan
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Michael Kiang
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - R Michael Bagby
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Sofia Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Romina Mizrahi
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.
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Plitman E, Chavez S, Nakajima S, Iwata Y, Chung JK, Caravaggio F, Kim J, Alshehri Y, Chakravarty MM, De Luca V, Remington G, Gerretsen P, Graff-Guerrero A. Striatal neurometabolite levels in patients with schizophrenia undergoing long-term antipsychotic treatment: A proton magnetic resonance spectroscopy and reliability study. Psychiatry Res Neuroimaging 2018; 273:16-24. [PMID: 29414127 DOI: 10.1016/j.pscychresns.2018.01.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Revised: 12/14/2017] [Accepted: 01/22/2018] [Indexed: 12/13/2022]
Abstract
Previous proton magnetic resonance spectroscopy (1H-MRS) studies have reported disrupted levels of various neurometabolites in patients with schizophrenia. An area of particular interest within this patient population is the striatum, which is highly implicated in the pathophysiology of schizophrenia. The present study examined neurometabolite levels in the striatum of 12 patients with schizophrenia receiving antipsychotic treatment for at least 1 year and 11 healthy controls using 3-Tesla 1H-MRS (PRESS, TE = 35 ms). Glutamate, glutamate+glutamine (Glx), myo-inositol, choline, N-acetylaspartate, and creatine levels were estimated using LCModel, and corrected for fraction of cerebrospinal fluid in the 1H-MRS voxel. Striatal neurometabolite levels were compared between groups. Multiple study visits permitted a reliability assessment for neurometabolite levels (days between paired 1H-MRS acquisitions: average = 90.33; range = 7-306). Striatal neurometabolite levels did not differ between groups. Within the whole sample, intraclass correlation coefficients for glutamate, Glx, myo-inositol, choline, and N-acetylaspartate were fair to excellent (0.576-0.847). The similarity in striatal neurometabolite levels between groups implies a marked difference from the antipsychotic-naïve first-episode state, especially in terms of glutamatergic neurometabolites, and might provide insight regarding illness progression and the influence of antipsychotic medication.
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Affiliation(s)
- Eric Plitman
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Sofia Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Shinichiro Nakajima
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Neuropsychiatry, Keio University, Tokyo, Japan
| | - Yusuke Iwata
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Jun Ku Chung
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Fernando Caravaggio
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Julia Kim
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Youssef Alshehri
- Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Departments of Psychiatry and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Vincenzo De Luca
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Schizophrenia Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Gary Remington
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Schizophrenia Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Philip Gerretsen
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
| | - Ariel Graff-Guerrero
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Geriatric Mental Health Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Campbell Institute Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
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27
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Boyd N, Berman H, Zhu J, Martin LJ, Yaffe MJ, Chavez S, Stanisz G, Hislop G, Chiarelli AM, Minkin S, Paterson AD. The origins of breast cancer associated with mammographic density: a testable biological hypothesis. Breast Cancer Res 2018. [PMID: 29514672 PMCID: PMC5842598 DOI: 10.1186/s13058-018-0941-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Background Our purpose is to develop a testable biological hypothesis to explain the known increased risk of breast cancer associated with extensive percent mammographic density (PMD), and to reconcile the apparent paradox that although PMD decreases with increasing age, breast cancer incidence increases. Methods We used the Moolgavkar model of carcinogenesis as a framework to examine the known biological properties of the breast tissue components associated with PMD that includes epithelium and stroma, in relation to the development of breast cancer. In this model, normal epithelial cells undergo a mutation to become intermediate cells, which, after further mutation, become malignant cells. A clone of such cells grows to become a tumor. The model also incorporates changes with age in the number of susceptible epithelial cells associated with menarche, parity, and menopause. We used measurements of the radiological properties of breast tissue in 4454 healthy subjects aged from 15 to 80+ years to estimate cumulative exposure to PMD (CBD) in the population, and we examined the association of CBD with the age-incidence curve of breast cancer in the population. Results Extensive PMD is associated with a greater number of breast epithelial cells, lobules, and fibroblasts, and greater amounts of collagen and extracellular matrix. The known biological properties of these tissue components may, singly or in combination, promote the acquisition of mutations by breast epithelial cells specified by the Moolgavkar model, and the subsequent growth of a clone of malignant cells to form a tumor. We also show that estimated CBD in the population from ages 15 to 80+ years is closely associated with the age-incidence curve of breast cancer in the population. Conclusions These findings are consistent with the hypothesis that the biological properties of the breast tissue components associated with PMD increase the probability of the transition of normal epithelium to malignant cells, and that the accumulation of mutations with CBD may influence the age-incidence curve of breast cancer. This hypothesis gives rise to several testable predictions. Electronic supplementary material The online version of this article (10.1186/s13058-018-0941-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Norman Boyd
- Princess Margaret Cancer Centre, 610 University Avenue, Room 9-502, Toronto, ON, M5G 2M9, Canada.
| | - Hal Berman
- Princess Margaret Cancer Centre, 610 University Avenue, Room 9-502, Toronto, ON, M5G 2M9, Canada
| | - Jie Zhu
- Princess Margaret Cancer Centre, 610 University Avenue, Room 9-502, Toronto, ON, M5G 2M9, Canada
| | - Lisa J Martin
- Princess Margaret Cancer Centre, 610 University Avenue, Room 9-502, Toronto, ON, M5G 2M9, Canada
| | - Martin J Yaffe
- Imaging Research, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Sofia Chavez
- Imaging Research, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Greg Stanisz
- Imaging Research, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | | | | | - Salomon Minkin
- Princess Margaret Cancer Centre, 610 University Avenue, Room 9-502, Toronto, ON, M5G 2M9, Canada
| | - Andrew D Paterson
- Genetics and Genome Biology, Hospital for Sick Children Research Institute, Toronto, ON, Canada.,Divisions of Epidemiology and Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
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Chavez S, Viviano J, Zamyadi M, Kingsley PB, Kochunov P, Strother S, Voineskos A. A novel DTI-QA tool: Automated metric extraction exploiting the sphericity of an agar filled phantom. Magn Reson Imaging 2018; 46:28-39. [PMID: 29054737 PMCID: PMC5800507 DOI: 10.1016/j.mri.2017.07.027] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Revised: 07/21/2017] [Accepted: 07/21/2017] [Indexed: 10/18/2022]
Abstract
PURPOSE To develop a quality assurance (QA) tool (acquisition guidelines and automated processing) for diffusion tensor imaging (DTI) data using a common agar-based phantom used for fMRI QA. The goal is to produce a comprehensive set of automated, sensitive and robust QA metrics. METHODS A readily available agar phantom was scanned with and without parallel imaging reconstruction. Other scanning parameters were matched to the human scans. A central slab made up of either a thick slice or an average of a few slices, was extracted and all processing was performed on that image. The proposed QA relies on the creation of two ROIs for processing: (i) a preset central circular region of interest (ccROI) and (ii) a signal mask for all images in the dataset. The ccROI enables computation of average signal for SNR calculations as well as average FA values. The production of the signal masks enables automated measurements of eddy current and B0 inhomogeneity induced distortions by exploiting the sphericity of the phantom. Also, the signal masks allow automated background localization to assess levels of Nyquist ghosting. RESULTS The proposed DTI-QA was shown to produce eleven metrics which are robust yet sensitive to image quality changes within site and differences across sites. It can be performed in a reasonable amount of scan time (~15min) and the code for automated processing has been made publicly available. CONCLUSIONS A novel DTI-QA tool has been proposed. It has been applied successfully on data from several scanners/platforms. The novelty lies in the exploitation of the sphericity of the phantom for distortion measurements. Other novel contributions are: the computation of an SNR value per gradient direction for the diffusion weighted images (DWIs) and an SNR value per non-DWI, an automated background detection for the Nyquist ghosting measurement and an error metric reflecting the contribution of EPI instability to the eddy current induced shape changes observed for DWIs.
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Affiliation(s)
- Sofia Chavez
- Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada.
| | | | | | - Peter B Kingsley
- Department of Radiology, North Shore University Hospital, Manhasset, USA
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland, School of Medicine, Baltimore, USA
| | - Stephen Strother
- Rotman Research Institute, Baycrest, Toronto, Canada; Medical Biophysics Department, University of Toronto, Toronto, Canada
| | - Aristotle Voineskos
- Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Canada
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29
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Caravaggio F, Iwata Y, Plitman E, Chavez S, Borlido C, Chung JK, Kim J, Agarwal SM, Gerretsen P, Remington G, Hahn M, Graff-Guerrero A. Reduced insulin sensitivity may be related to less striatal glutamate: An 1H-MRS study in healthy non-obese humans. Eur Neuropsychopharmacol 2018; 28:285-296. [PMID: 29269206 DOI: 10.1016/j.euroneuro.2017.12.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2017] [Revised: 11/22/2017] [Accepted: 12/02/2017] [Indexed: 10/18/2022]
Abstract
Levels of striatal dopamine (DA) may be positively correlated with levels of striatal glutamate (Glu). While reduced insulin sensitivity (%S) has been associated with reduced striatal DA levels in healthy non-obese persons, whether reduced %S is also associated with reduced striatal Glu levels has not yet been established. Using 1H-MRS, we measured levels of several neurometabolites in the striatum and dorsolateral prefrontal cortex (DLPFC) of seventeen healthy non-obese persons (9 female, mean age: 28.35 ± 9.53). Insulin sensitivity was estimated for each subject from fasting plasma glucose and insulin using the Homeostasis Model Assessment II. We hypothesized that %S would be positively related with levels of Glu and Glu + glutamine (Glx) in the striatum. Exploratory analyses were also conducted between other fasting markers of metabolic health and neurometabolites measured with 1H-MRS. In the right striatum, %S was positively correlated with levels of Glu (r(15) = .49, p = .04) and Glx (r(15) = .50, p = .04). In the left striatum, there was a trend positive correlation between %S and Glu (r(15) = .46, p = .06), but not Glx levels (r(15) = .20, p = .44). The relationships between %S and striatal Glu levels remained after controlling for age, sex, and BMI (right: r(12) = .73, β = .52, t = 2.55, p = .03; left: (r(12) = .63, β = .53, t = 2.25, p = .04) These preliminary findings suggest that %S may be related to markers of glutamatergic functioning in the striatum of healthy non-obese persons. These findings warrant replication in larger samples and extension into neuropsychiatric populations where altered striatal DA, Glu, and %S are implicated.
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Affiliation(s)
- Fernando Caravaggio
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Department of Psychiatry, University of Toronto, 250 College Street, Toronto, Ontario, Canada M5T 1R8
| | - Yusuke Iwata
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8
| | - Eric Plitman
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Institute of Medical Science, University of Toronto, 2374 Medical Sciences Building, 1 King's College Circle, Toronto, Ontario, Canada M5S 1A8
| | - Sofia Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Department of Psychiatry, University of Toronto, 250 College Street, Toronto, Ontario, Canada M5T 1R8
| | - Carol Borlido
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8
| | - Jun Ku Chung
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Institute of Medical Science, University of Toronto, 2374 Medical Sciences Building, 1 King's College Circle, Toronto, Ontario, Canada M5S 1A8
| | - Julia Kim
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Institute of Medical Science, University of Toronto, 2374 Medical Sciences Building, 1 King's College Circle, Toronto, Ontario, Canada M5S 1A8
| | - Sri Mahavir Agarwal
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8
| | - Philip Gerretsen
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Department of Psychiatry, University of Toronto, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Institute of Medical Science, University of Toronto, 2374 Medical Sciences Building, 1 King's College Circle, Toronto, Ontario, Canada M5S 1A8
| | - Gary Remington
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Department of Psychiatry, University of Toronto, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Institute of Medical Science, University of Toronto, 2374 Medical Sciences Building, 1 King's College Circle, Toronto, Ontario, Canada M5S 1A8
| | - Margaret Hahn
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Department of Psychiatry, University of Toronto, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Institute of Medical Science, University of Toronto, 2374 Medical Sciences Building, 1 King's College Circle, Toronto, Ontario, Canada M5S 1A8
| | - Ariel Graff-Guerrero
- Research Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Department of Psychiatry, University of Toronto, 250 College Street, Toronto, Ontario, Canada M5T 1R8; Institute of Medical Science, University of Toronto, 2374 Medical Sciences Building, 1 King's College Circle, Toronto, Ontario, Canada M5S 1A8.
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Kochunov P, Dickie EW, Viviano JD, Turner J, Kingsley PB, Jahanshad N, Thompson PM, Ryan MC, Fieremans E, Novikov D, Veraart J, Hong EL, Malhotra AK, Buchanan RW, Chavez S, Voineskos AN. Integration of routine QA data into mega-analysis may improve quality and sensitivity of multisite diffusion tensor imaging studies. Hum Brain Mapp 2017; 39:1015-1023. [PMID: 29181875 DOI: 10.1002/hbm.23900] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 11/07/2017] [Accepted: 11/16/2017] [Indexed: 12/14/2022] Open
Abstract
A novel mega-analytical approach that reduced methodological variance was evaluated using a multisite diffusion tensor imaging (DTI) fractional anisotropy (FA) data by comparing white matter integrity in people with schizophrenia to controls. Methodological variance was reduced through regression of variance captured from quality assurance (QA) and by using Marchenko-Pastur Principal Component Analysis (MP-PCA) denoising. N = 192 (119 patients/73 controls) data sets were collected at three sites equipped with 3T MRI systems: GE MR750, GE HDx, and Siemens Trio. DTI protocol included five b = 0 and 60 diffusion-sensitized gradient directions (b = 1,000 s/mm2 ). In-house DTI QA protocol data was acquired weekly using a uniform phantom; factor analysis was used to distil into two orthogonal QA factors related to: SNR and FA. They were used as site-specific covariates to perform mega-analytic data aggregation. The effect size of patient-control differences was compared to these reported by the enhancing neuro imaging genetics meta-analysis (ENIGMA) consortium before and after regressing QA variance. Impact of MP-PCA filtering was evaluated likewise. QA-factors explained ∼3-4% variance in the whole-brain average FA values per site. Regression of QA factors improved the effect size of schizophrenia on whole brain average FA values-from Cohen's d = .53 to .57-and improved the agreement between the regional pattern of FA differences observed in this study versus ENIGMA from r = .54 to .70. Application of MP-PCA-denoising further improved the agreement to r = .81. Regression of methodological variances captured by routine QA and advanced denoising that led to a better agreement with a large mega-analytic study.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore
| | - Erin W Dickie
- Centre for Addiction and Mental Health, Toronto, Canada
| | | | - Jessica Turner
- Department of Psychology, Georgia State University, Atlanta, Georgia
| | - Peter B Kingsley
- Department of Radiology, North Shore University Hospital, Manhasset, New York
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Meghann C Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore
| | - Els Fieremans
- Department of Radiology, New York University School of Medicine, New York, New York
| | - Dmitry Novikov
- Department of Radiology, New York University School of Medicine, New York, New York
| | - Jelle Veraart
- Department of Radiology, New York University School of Medicine, New York, New York
| | - Elliot L Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore
| | - Anil K Malhotra
- Department of Radiology, North Shore University Hospital, Manhasset, New York
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore
| | - Sofia Chavez
- Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Canada
| | - Aristotle N Voineskos
- Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Canada
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Mehrabian H, Desmond KL, Chavez S, Bailey C, Rola R, Sahgal A, Czarnota GJ, Soliman H, Martel AL, Stanisz GJ. Water Exchange Rate Constant as a Biomarker of Treatment Efficacy in Patients With Brain Metastases Undergoing Stereotactic Radiosurgery. Int J Radiat Oncol Biol Phys 2017; 98:47-55. [PMID: 28258890 DOI: 10.1016/j.ijrobp.2017.01.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Revised: 12/12/2016] [Accepted: 01/02/2017] [Indexed: 10/20/2022]
Abstract
PURPOSE This study was designed to evaluate whether changes in metastatic brain tumors after stereotactic radiosurgery (SRS) can be seen with quantitative MRI early after treatment. METHODS AND MATERIALS Using contrast-enhanced MRI, a 3-water-compartment tissue model consisting of intracellular (I), extracellular-extravascular (E), and vascular (V) compartments was used to assess the intra-extracellular water exchange rate constant (kIE), efflux rate constant (kep), and water compartment volume fractions (M0,I, M0,E, M0,V). In this prospective study, 19 patients were MRI-scanned before treatment and 1 week and 1 month after SRS. The change in model parameters between the pretreatment and 1-week posttreatment scans was correlated to the change in tumor volume between pretreatment and 1-month posttreatment scans. RESULTS At 1 week kIE differentiated (P<.001) tumors that had partial response from tumors with stable and progressive disease, and a high correlation (R=-0.76, P<.001) was observed between early changes in the kIE and tumor volume change 1 month after treatment. Other model parameters had lower correlation (M0,E) or no correlation (kep, M0,V). CONCLUSIONS This is the first study that measured kIE early after SRS, and it found that early changes in kIE (1 week after treatment) highly correlated with long-term tumor response and could predict the extent of tumor shrinkage at 1 month after SRS.
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Affiliation(s)
- Hatef Mehrabian
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.
| | - Kimberly L Desmond
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Sofia Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Colleen Bailey
- Computer Science Department, University College London, London, United Kingdom
| | - Radoslaw Rola
- Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
| | - Arjun Sahgal
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada; Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Gregory J Czarnota
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada; Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Hany Soliman
- Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Anne L Martel
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Greg J Stanisz
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada; Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
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Desmond KL, Mehrabian H, Chavez S, Sahgal A, Soliman H, Rola R, Stanisz GJ. Chemical exchange saturation transfer for predicting response to stereotactic radiosurgery in human brain metastasis. Magn Reson Med 2016; 78:1110-1120. [PMID: 27690156 DOI: 10.1002/mrm.26470] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Revised: 08/23/2016] [Accepted: 08/29/2016] [Indexed: 12/19/2022]
Abstract
PURPOSE The purpose of this work was to determine the predictive value of chemical exchange saturation transfer (CEST) metrics in brain metastases treated with stereotactic radiosurgery (SRS). METHODS CEST spectra at a radiofrequency power of 0.52 µT were collected on a 3 Tesla (T) magnetic resonance imaging from 25 patients at three time points: pretreatment, 1 week, and 1 month post-treatment. Amide proton transfer-weighted images and maps of the amplitude and width of Lorentzian-shaped CEST peaks and the relaxation-compensated AREX metric were constructed at the offset frequencies of amide, amine, and relayed nuclear Overhauser effect (NOE) from aliphatic groups as well as the broad magnetization transfer effect. Pretreatment CEST metrics, as well as CEST metric changes at 1 week post-treatment, were compared to changes in tumor volume at 1 month. RESULTS Significant (P < 0.05) 1-week predictive metrics included NOE peak amplitude (R = 0.69) in normal-appearing white matter (NAWM) and width (R = -0.55) in tumor. Baseline NOE in contralateral NAWM was negatively correlated (R = -0.69) with volume changes at 1 month. Metrics-defined outside tumor margins had higher correlation with volume changes than tumor regions of interest. CONCLUSION CEST metrics, in particular, the NOE peak amplitude, can predict volume changes 1 month post-SRS. Magn Reson Med 78:1110-1120, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Kimberly L Desmond
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Hatef Mehrabian
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Sofia Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Arjun Sahgal
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Hany Soliman
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Radoslaw Rola
- Department of Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
| | - Greg J Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Department of Neurosurgery and Pediatric Neurosurgery, Medical University, Lublin, Poland
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Plitman E, de la Fuente-Sandoval C, Reyes-Madrigal F, Chavez S, Gómez-Cruz G, León-Ortiz P, Graff-Guerrero A. Elevated Myo-Inositol, Choline, and Glutamate Levels in the Associative Striatum of Antipsychotic-Naive Patients With First-Episode Psychosis: A Proton Magnetic Resonance Spectroscopy Study With Implications for Glial Dysfunction. Schizophr Bull 2016; 42:415-24. [PMID: 26320195 PMCID: PMC4753594 DOI: 10.1093/schbul/sbv118] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Glial disturbances are highly implicated in the pathophysiology of schizophrenia and may be linked with glutamatergic dysregulation. Myo-inositol (mI), a putative marker of glial cells, and choline (Cho), representative of membrane turnover, are both present in larger concentrations within glial cells than in neurons, and their elevation is often interpreted to reflect glial activation. Proton magnetic resonance spectroscopy ((1)H-MRS) allows for the evaluation of mI, Cho, glutamate, glutamate + glutamine (Glx), and N-acetylaspartate (NAA). A collective investigation of these measures in antipsychotic-naive patients experiencing their first nonaffective episode of psychosis (FEP) can improve the understanding of glial dysfunction and its implications in the early stages of schizophrenia. 3-Tesla (1)H-MRS (echo time = 35 ms) was performed in 60 antipsychotic-naive patients with FEP and 60 age- and sex-matched healthy controls. mI, Cho, glutamate, Glx, and NAA were estimated using LCModel and corrected for cerebrospinal fluid composition within the voxel. mI, Cho, and glutamate were elevated in the FEP group. After correction for multiple comparisons, mI positively correlated with grandiosity. The relationships between mI and glutamate, and Cho and glutamate, were more positive in the FEP group. These findings are suggestive of glial activation in the absence of neuronal loss and may thereby provide support for the presence of a neuroinflammatory process within the early stages of schizophrenia. Dysregulation of glial function might result in the disruption of glutamatergic neurotransmission, which may influence positive symptomatology in patients with FEP.
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Affiliation(s)
- Eric Plitman
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada;,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Camilo de la Fuente-Sandoval
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico; Neuropsychiatry Department, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico;
| | - Francisco Reyes-Madrigal
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Sofia Chavez
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada;,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Gladys Gómez-Cruz
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Pablo León-Ortiz
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico;,Department of Education, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Ariel Graff-Guerrero
- Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada;,Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada;,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada;,Geriatric Mental Health Division, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada;,Campbell Institute Research Program, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada
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Vera M, Chavez S, Rubio C, Reijo Pera R, Simon C. Prediction model for aneuploidy in early human embryos based on the transcriptomic signature. Fertil Steril 2014. [DOI: 10.1016/j.fertnstert.2014.07.078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Hennessey S, Huszti E, Gunasekura A, Salleh A, Martin L, Minkin S, Chavez S, Boyd NF. Bilateral symmetry of breast tissue composition by magnetic resonance in young women and adults. Cancer Causes Control 2014; 25:491-7. [PMID: 24477331 PMCID: PMC3942631 DOI: 10.1007/s10552-014-0351-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2013] [Accepted: 01/22/2014] [Indexed: 11/25/2022]
Abstract
BACKGROUND Some reports suggest that there is a slightly higher frequency of breast cancer in the left breast compared with the right in middle-aged women. The reasons for this association are unknown. The water and fat content of both breasts was compared using magnetic resonance (MR). Breast water by MR reflects fibro-glandular tissue and is strongly positively correlated with percent mammographic density, a strong risk factor for breast cancer. METHODS Magnetic resonance was used to measure fat and water content of the breast in 400 young women aged 15-30 years and a random sample of 100 of their mothers. All MR examinations were carried out using a 1.5T MR system, and 45 contiguous slices were obtained in the sagittal plane. One reader identified the breast tissue in the image, and subsequently, fat and water content was calculated using a three-point Dixon technique. Left- and right-sided images were read independently in random order. RESULTS In young women, mean percent water was on average 0.84 % higher in the right compared with the left breast (p < 0.001) and total breast water was on average 6.42 cm(3) greater on the right side (p < 0.001). In mothers, there were no significant differences in any breast measure between right and left sides. CONCLUSION The small differences in breast tissue composition in young women are unlikely to be associated with large differences in breast cancer risk between sides. The reported excess of left-sided breast cancer in older women is unlikely to be explained by differences in breast tissue composition.
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Affiliation(s)
- S. Hennessey
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, 10-415 610 University Ave., Toronto, ON Canada
| | - E. Huszti
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, 10-415 610 University Ave., Toronto, ON Canada
| | - A. Gunasekura
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, 10-415 610 University Ave., Toronto, ON Canada
| | - A. Salleh
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, 10-415 610 University Ave., Toronto, ON Canada
| | - L. Martin
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, 10-415 610 University Ave., Toronto, ON Canada
| | - S. Minkin
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, 10-415 610 University Ave., Toronto, ON Canada
| | - S. Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON M4T 1C8 Canada
| | - N. F. Boyd
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, 10-415 610 University Ave., Toronto, ON Canada
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Chavez S, Stanisz G. Comparing average breast fat content results from two different protocols at 1.5T and 3T: can the data be pooled? J Magn Reson Imaging 2013; 40:890-8. [PMID: 24989130 DOI: 10.1002/jmri.24452] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2013] [Accepted: 09/08/2013] [Indexed: 11/07/2022] Open
Abstract
PURPOSE To compare the total breast fat content computed from two separate studies, performed on different scanners and with different protocols, with the goal of defining a relationship to allow pooling the data. MATERIALS AND METHODS Twelve healthy volunteer women were scanned with two different protocols on the same day. The protocols differed in four important aspects: vendors (GE vs. Philips), scanner main magnetic field strengths (1.5T vs. 3T), pulse sequences (2D fast spin-echo vs. 3D spoiled gradient-echo), and water/fat separation techniques. The resulting water and fat maps were processed with in-house software to extract breast tissue slice-wise. Percent fat content was calculated for each breast, per subject. RESULTS Total percent fat contents (averaged across both breasts) resulting from both protocols were plotted against each other, on a subject-by-subject basis, revealing a strong correlation (R(2) > 0.99), with an overestimation of the fat content from Protocol 1 relative to Protocol 2. The proposed T2 TE-correction for Protocol 1 improves the correlation while decreasing the discrepancy between protocols. CONCLUSION Total breast fat content of healthy women resulting from the two protocols can be pooled using a linear relationship. The proposed T2 TE-corrected Protocol 1 is expected to yield accurate fat content.
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Affiliation(s)
- Sofia Chavez
- Centre for Addiction and Mental Health, Research Imaging Centre, Toronto, ON, Canada; University of Toronto, Psychiatry, Toronto, ON, Canada
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Winterburn JL, Pruessner JC, Chavez S, Schira MM, Lobaugh NJ, Voineskos AN, Chakravarty MM. A novel in vivo atlas of human hippocampal subfields using high-resolution 3T magnetic resonance imaging. Neuroimage 2013; 74:254-65. [DOI: 10.1016/j.neuroimage.2013.02.003] [Citation(s) in RCA: 157] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2012] [Revised: 01/28/2013] [Accepted: 02/03/2013] [Indexed: 10/27/2022] Open
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Chavez S, Stanisz GJ. A novel method for simultaneous 3D B(1) and T(1) mapping: the method of slopes (MoS). NMR Biomed 2012; 25:1043-1055. [PMID: 22368092 DOI: 10.1002/nbm.2769] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2011] [Revised: 11/15/2011] [Accepted: 11/29/2011] [Indexed: 05/31/2023]
Abstract
A novel three-dimensional simultaneous B(1) and T(1) mapping method is introduced: the method of slopes (MoS). The linearity of the spoiled gradient recalled echo (SPGR) signal vs flip angle relation is exploited: B(1) mapping is achieved by a two-point extrapolation to signal null with a correction scheme while T(1) mapping uses the slopes of the SPGR signal vs flip angle curves near the origin and near the signal null. This new method improves upon the existing variable flip angle (VFA) T(1)-mapping method in that (i) consistency between B(1) and T(1) maps is ensured (ii) the sampling scheme is T(1)-independent (iii) the noise bias and singularity, associated with using a linear form for the SPGR signal equation, is eliminated by using the full equation. The method is shown to yield accurate and robust results via simulations. Initial estimates of B(1) and T(1) values are obtained from three data points via simple computations and straight line approximations. Initial estimates of B(1) values, for a range of values, are shown to be accurate due to the proposed B(1) correction scheme. The accuracy and robustness of T(1) values is achieved via a non-linear fitting algorithm which includes a fourth data point sampled at high SNR. The MoS was validated by comparing resulting B(1) and T(1) maps with those obtained using other standard methods. Finally, the ability to obtain brain B(1) and T(1) maps using the MoS was demonstrated by in vivo experiments. The MoS is expected to perform well on other motion-free anatomical regions as well.
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Affiliation(s)
- Sofia Chavez
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.
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Fourati Ben Mustapha S, Khrouf M, Kacem Ben Rejeb K, Elloumi Chaabene H, Merdassi G, Wahbi D, Ben Meftah M, Zhioua F, Zhioua A, Azzarello A, Host T, Mikkelsen AL, Theofanakis CP, Dinopoulou V, Mavrogianni D, Partsinevelos GA, Drakakis P, Stefanidis K, Bletsa A, Loutradis D, Rienzi L, Cobo A, Paffoni A, Scarduelli C, Capalbo A, Garrido N, Remohi J, Ragni G, Ubaldi FM, Herrer R, Quera M, GIL E, Serna J, Grondahl ML, Bogstad J, Agerholm IE, Lemmen JG, Bentin-Ley U, Lundstrom P, Kesmodel US, Raaschou-Jensen M, Ladelund S, Guzman L, Ortega C, Albuz FK, Gilchrist RB, Devroey P, Smitz J, De Vos M, Bielanska M, Leveille MC, Borghi E, Magli MC, Figueroa MJ, Mascaretti G, Ferraretti AP, Gianaroli L, Szlit E, Leocata Nieto F, Maggiotto G, Arenas G, Tarducci Bonfiglio N, Ahumada A, Asch R, Sciorio R, Dayoub N, Thong J, Pickering S, Ten J, Carracedo MA, Guerrero J, Rodriguez-Arnedo A, Llacer J, Bernabeu R, Tatone C, Heizenrieder T, Di Emidio G, Treffon P, Seidel T, Eichenlaub-Ritter U, Cortezzi SS, Cabral EC, Ferreira CR, Trevisan MG, Figueira RCS, Braga DPAF, Eberlin MN, Iaconelli Jr. A, Borges Jr. E, Zabala A, Pessino T, Blanco L, Rey Valzacchi G, Leocata F, Ahumada A, Vanden Meerschaut F, Heindryckx B, Qian C, Deforce D, Leybaert L, De Sutter P, De las Heras M, De Pablo JL, Navarro B, Agirregoikoa JA, Barrenetxea G, Cruz M, Perez-Cano I, Gadea B, Herrero J, Martinez M, Roldan M, Munoz M, Pellicer A, Meseguer M, Munoz M, Cruz M, Roldan M, Gadea B, Galindo N, Martinez M, Pellicer A, Meseguer M, Perez-Cano I, Scarselli F, Alviggi E, Colasante A, Minasi MG, Rubino P, Lobascio M, Ferrero S, Litwicka K, Varricchio MT, Giannini P, Piscitelli P, Franco G, Zavaglia D, Nagy ZP, Greco E, Urner F, Wirthner D, Murisier F, Mock P, Germond M, Amorocho Llanos B, Calderon G, Lopez D, Fernandez L, Nicolas M, Landeras J, Finn-Sell SL, Leandri R, Fleming TP, Macklon NS, Cheong YC, Eckert JJ, Lee JH, Jung YJ, Hwang HK, Kang A, An SJ, Jung JY, Kwon HC, Lee SJ, Palini S, Zolla L, De Stefani S, Scala V, D'Alessandro A, Polli V, Rocchi P, Tiezzi A, Pelosi E, Dusi L, Bulletti C, Fadini R, Lain M, Mignini Renzini M, Brambillasca F, Coticchio G, Merola M, Guglielmo MC, Dal Canto M, Figueira R, Setti AS, Braga DPAF, Iaconelli Jr. A, Borges Jr. E, Worrilow KC, Uzochukwu CD, Eid S, Le Gac S, Esteves TC, van Rossem F, van den Berg A, Boiani M, Kasapi E, Panagiotidis Y, Goudakou M, Papatheodorou A, Pasadaki T, Prapas N, Prapas Y, Panagiotidis Y, Kasapi E, Goudakou M, Papatheodorou A, Pasadaki T, Vanderzwalmen P, Prapas N, Prapas Y, Norasing S, Atchajaroensatit P, Tawiwong W, Thepmanee O, Saenlao S, Aojanepong J, Hunsajarupan P, Sajjachareonpong K, Punyatanasakchai P, Maneepalviratn S, Jetsawangsri U, Herrero J, Cruz M, Tejera A, Rubio I, Romero JL, Meseguer M, Nordhoff V, Schlatt S, Schuring AN, Kiesel L, Kliesch S, Azambuja R, Okada L, Lazzari V, Dorfman L, Michelon J, Badalotti M, Badalotti F, Petracco A, Schwarzer C, Esteves TC, Nordhoff V, Schlatt S, Boiani M, Versieren K, Heindryckx B, De Croo I, Lierman S, De Vos W, Van den Abbeel E, Gerris J, De Sutter P, Milacic I, Borogovac D, Veljkovic M, Arsic B, Jovic Bojovic D, Lekic D, Pavlovic D, Garalejic E, Guglielmo MC, Coticchio G, Albertini DF, Dal Canto M, Brambillasca F, Mignini Renzini M, De Ponti E, Fadini R, Sanges F, Talevi R, Capalbo A, Papini L, Mollo V, Ubaldi FM, Rienzi LF, Gualtieri R, Albuz FK, Guzman L, Orteg C, Gilchrist RB, Devroey P, De Vos M, Smitz J, Choi J, Lee H, Ku S, Kim S, Choi Y, Kim J, Moon S, Demilly E, Assou S, Moussaddykine S, Dechaud H, Hamamah S, Takisawa T, Doshida M, Hattori H, Nakamura Y, Kyoya T, Shibuya Y, Nakajo Y, Tasaka A, Toya M, Kyono K, Novo S, Penon O, Gomez R, Barrios L, Duch M, Santalo J, Esteve J, Nogues C, Plaza JA, Perez-Garcia L, Ibanez E, Chavez S, Loewke K, Behr B, Reijo Pera R, Huang S, Wang H, Soong Y, Chang C, Okimura T, Kuwayama M, Mori C, Morita M, Uchiyama K, Aono F, Kato K, Takehara Y, Kato O, Minasi M, Casciani V, Scarselli F, Rubino P, Colasante A, Arizzi L, Litwicka K, Ferrero S, Mencacci C, Piscitelli C, Giannini P, Cucinelli F, Tocci A, Nagy ZP, Greco E, Wydooghe E, Vandaele L, Dewulf J, Van den Abbeel E, De Sutter P, Van Soom A, Moon JH, Son WY, Mahfoudh A, Henderson S, Jin SG, Shalom-Paz E, Dahan M, Holzer H, Mahmoud K, Triki-Hmam C, Terras K, Zhioua F, Hfaiedh T, Ben Aribia MH, Otsubo H, Egashira A, Tanaka K, Matsuguma T, Murakami M, Murakami K, Otsuka M, Yoshioka N, Araki Y, Kuramoto T, Smit JG, Sterrenburg MD, Eijkemans MJC, Al-Inany HG, Youssef MAFM, Broekmans FJM, Willoughby K, DiPaolo L, Deys L, Lagunov A, Amin S, Faghih M, Hughes E, Karnis M, Ashkar F, King WA, Neal MS, Antonova I, Veleva L, Petkova L, Shterev A, Nogales C, Martinez E, Ariza M, Cernuda D, Gaytan M, Linan A, Guillen A, Bronet F, Cottin V, Fabian D, Allemann F, Koller A, Spira JC, Agudo D, Martinez-Burgos M, Arnanz A, Basile N, Rodriguez A, Bronet F, Cho YS, Filioli Uranio M, Ambruosi B, Paternoster MS, Totaro P, Sardanelli AM, Dell'Aquila ME, Zollner U, Hofmann T, Zollner KP, Kovacic B, Roglic P, Vlaisavljevic V, Sole M, Santalo J, Boada M, Coroleu B, Veiga A, Martiny G, Molinari M, Revelli A, Chimote NM, Chimote M, Mehta B, Chimote NN, Sheikh N, Nath N, Mukherjee A, Rakic K, Reljic M, Kovacic B, Vlaisavljevic V, Ingerslev HJ, Kirkegaard K, Hindkjaer J, Grondahl ML, Kesmodel US, Agerholm I, Kitasaka H, Fukunaga N, Nagai R, Yoshimura T, Tamura F, Kitamura K, Hasegawa N, Nakayama K, Katou M, Itoi F, Asano E, Deguchi N, Ooyama K, Hashiba Y, Asada Y, Michaeli M, Rotfarb N, Karchovsky E, Ruzov O, Atamny R, Slush K, Fainaru O, Ellenbogen A, Chekuri S, Chaisrisawatsuk T, Chen P, Pangestu M, Jansen S, Catt S, Molinari E, Racca C, Revelli A, Ryu C, Kang S, Lee J, Chung D, Roh S, Chi H, Yokota Y, Yokota M, Yokota H, Sato S, Nakagawa M, Komatsubara M, Makita M, Araki Y, Yoshimura T, Asada Y, Fukunaga N, Nagai R, Kitasaka H, Itoi F, Tamura F, Kitamura K, Hasegawa N, Katou M, Nakayama K, Asano E, Deguchi N, Oyama K, Hashiba Y, Naruse K, Kilani S, Chapman MG, Kwik M, Chapman M, Guven S, Odaci E, Yildirim O, Kart C, Unsal MA, Yulug E, Isachenko E, Maettner R, Strehler E, Isachenko V, Hancke K, Kreienberg R, Sterzik K, Coticchio G, Guglielmo MC, Dal Canto M, Albertini DF, Brambillasca F, Mignini Renzini M, Fadini R, Zheng XY, Wang LN, Liu P, Qiao J, Inoue F, Dashtizad M, Wahid H, Rosnina Y, Daliri M, Hajarian H, Akbarpour M, Abbas Mazni O, Knez K, Tomaevic T, Vrtacnik Bokal E, Zorn B, Virant Klun I, Koster M, Liebenthron J, Nicolov A, van der Ven K, van der Ven H, Montag M, Fayazi M, Salehnia M, Beigi Boroujeni M, Khansarinejad B, Deignan K, Emerson G, Mocanu E, Wang JJ, Andonov M, Linara E, Ahuja KK, Nachef S, Figueira RCS, Braga DPAF, Setti AS, Iaconelli Jr. A, Pasqualotto FF, Borges Jr. E, Pasqualotto E, Borges Jr. E, Pasqualotto FF, Chang CC, Bernal DP, Elliott TA, Shapiro DB, Toledo AA, Nagy ZP, Economou K, Davies S, Argyrou M, Doriza S, Sisi P, Moschopoulou M, Karagianni A, Mendorou C, Polidoropoulos N, Papanicopoulos C, Stefanis P, Karamalegos C, Cazlaris H, Koutsilieris M, Mastrominas M, Gotts S, Doshi A, Harper J, Serhal P, Borini A, Guzeloglu-Kayisli O, Bianchi V, Seli E, Bianchi V, Lappi M, Bonu MA, Borini A, Mizuta S, Hashimoto H, Kuroda Y, Matsumoto Y, Mizusawa Y, Ogata S, Yamada S, Kokeguchi S, Noda Y, Shiotani M, Stojkovic M, Ilic M, Markovic N, Stojkovic P, Feng G, Zhang B, Zhou H, Zhou L, Gan X, Qin X, Shu J, Wu F, Molina Botella I, Lazaro Ibanez E, Debon Aucejo A, Pertusa J, Fernandez Colom PJ, Pellicer A, Li C, Zhang Y, Cui Y, Zhao H, Liu J, Oliveira JBA, Petersen CG, Mauri AL, Massaro FC, Silva LFI, Ricci J, Cavagna M, Pontes A, Vagnini LD, Baruffi RLR, Franco Jr. JG, Massaro FC, Petersen CG, Vagnini LD, Mauri AL, Silva LFI, Felipe V, Cavagna M, Pontes A, Baruffi RLR, Oliveira JBA, Franco Jr. JG, Vilela M, Tiveron M, Lombardi C, Viglierchio MI, Marconi G, Rawe V, Wale PL, Gardner DK, Nakagawa K, Sugiyama R, Nishi Y, Kuribayashi Y, Jyuen H, Yamashiro E, Shirai A, Sugiyama R, Inoue M, Salehnia M, Hovatta O, Tohonen V, Inzunza J, Parmegiani L, Cognigni GE, Bernardi S, Ciampaglia W, Infante FE, Tabarelli de Fatis C, Pocognoli P, Arnone A, Maccarini AM, Troilo E, Filicori M, Radwan P, Polac I, Borowiecka M, Bijak M, Radwan M. POSTER VIEWING SESSION - EMBRYOLOGY. Hum Reprod 2011. [DOI: 10.1093/humrep/26.s1.79] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Abstract
Echo-planar imaging (EPI) -based diffusion tensor imaging (DTI) is particularly prone to spike noise. However, existing spike noise correction methods are impractical for corrupted DTI data because the methods correct the complex MRI signal, which is not usually stored on clinical MRI systems. The present work describes a novel Outlier Detection De-spiking technique (ODD) that consists of three steps: detection, localization, and correction. Using automated outlier detection schemes, ODD exploits the data redundancy available in DTI data sets that are acquired with a minimum of six different diffusion-weighted images (DWIs) with similar signal and noise properties. A mathematical formulation, describing the effects of spike noise on magnitude images, yields appropriate measures for an outlier detection scheme used for spike detection while a normalization-dependent outlier detection scheme is used for spike localization. ODD performs accurately on diverse DTI data sets corrupted by spike noise and can be used for automated control of DTI data quality. ODD can also be extended to other MRI applications with data redundancy, such as dynamic imaging and functional MRI.
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Affiliation(s)
- S Chavez
- Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.
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Szilagyi G, Scott CJ, Chavez S, Black SE. IC‐P‐129: Magnetic Resonance Spectroscopy (MRS) analysis in Alzheimer's disease: A novel approach for integrating metabolite spectra, tissue segmentation and perfusion data. Alzheimers Dement 2009. [DOI: 10.1016/j.jalz.2009.05.101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Gregory Szilagyi
- Sunnybrook Health Sciences CentreTorontoONCanada
- University of TorontoTorontoONCanada
| | | | - Sofia Chavez
- Sunnybrook Health Sciences CentreTorontoONCanada
| | - Sandra E. Black
- Sunnybrook Health Sciences CentreTorontoONCanada
- University of TorontoTorontoONCanada
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Szilagyi G, Scott CJ, Chavez S, Black SE. P1‐134: Magnetic Resonance Spectroscopy (MRS) analysis in Alzheimer's disease ‐ a novel approach for integrating metabolite spectra, tissue segmentation and perfusion data. Alzheimers Dement 2009. [DOI: 10.1016/j.jalz.2009.04.139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Gregory Szilagyi
- Sunnybrook Health Sciences CentreTorontoONCanada
- University of TorontoTorontoONCanada
| | | | - Sofia Chavez
- Sunnybrook Health Sciences CentreTorontoONCanada
| | - Sandra E. Black
- Sunnybrook Health Sciences CentreTorontoONCanada
- University of TorontoTorontoONCanada
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Boyd N, Martin L, Chavez S, Gunasekara A, Salleh A, Melnichouk O, Yaffe M, Friedenreich C, Minkin S, Bronskill M. Breast-tissue composition and other risk factors for breast cancer in young women: a cross-sectional study. Lancet Oncol 2009; 10:569-80. [PMID: 19409844 DOI: 10.1016/s1470-2045(09)70078-6] [Citation(s) in RCA: 150] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
BACKGROUND Mammographic density is a heritable quantitative trait and is a strong risk factor for breast cancer in middle-aged and older women. However, little is known about the development of mammographic density in early life. We used MRI to measure the water content of the breast, which provides a measurement of the fibro-glandular content of breast tissue with similar accuracy to mammography, but without the attendant exposure to radiation. METHODS Between December, 2003, and December, 2007, we recruited 400 young women, aged 15-30 years, and their mothers. We used MRI scans to measure daughters' breast water and fat, and on the same day obtained blood for hormone assays in the follicular phase of the menstrual cycle for each young woman. Mothers underwent mammography (n=356), and a random sample (n=100) also consented to have a breast MRI scan. FINDINGS In mothers, per cent water-as measured by MRI-was strongly correlated with per cent mammographic density (r=0.85). Per cent water in daughters (median 44.8%) was significantly higher than in mothers (median 27.8%; p<0.0001), and was independently inversely associated with both their age (p=0.04) and weight (p<0.0001), and positively associated with their height (p<0.0001) and their mothers' per cent mammographic density (p<0.0001). Serum growth hormone concentrations, adjusted for covariates, were positively associated with per cent breast water (p=0.001) in a subgroup of young women (n=280) who had not used oral contraceptives within 6 months. INTERPRETATION Per cent breast water was greatest during the ages when women are most susceptible to breast carcinogens, and was associated with weight, height, and mother's breast-tissue characteristics, and with serum concentrations of growth hormone: a breast mitogen that also mediates postnatal somatic growth. Mammographic density in middle age might partly be the result of genetic factors that affect growth and development in early life. FUNDING Canadian Breast Cancer Research Alliance.
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Affiliation(s)
- Norman Boyd
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, ON, Canada.
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Martin L, Chavez S, Gunasekara A, Salleh A, Melnichouk O, Yaffe M, Minkin S, Bronskill M, Boyd N. Abstract A123: Serum levels of hormones and breast tissue composition in young women. Cancer Prev Res (Phila) 2008. [DOI: 10.1158/1940-6207.prev-08-a123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
A123
Background
Percent mammographic density (PMD) is a strong and heritable risk factor for breast cancer with characteristics that suggest it may be a marker of susceptibility to the disease. We have examined serum hormone levels and other factors associated with breast tissue composition in young women, when susceptibility to breast carcinogens is greatest.
Methods
In 400 young women aged 15-30 years we obtained quantitative measures of breast water, which reflects fibro-glandular tissue, and breast fat using magnetic resonance (MR), and collected anthropometric and other data. All examinations were performed in the follicular phase of the menstrual cycle and fasting blood samples for hormone assays were obtained on the morning of the MR examination.
Results
Serum levels of growth hormone (GH) and sex hormone binding globulin (SHBG) were positively associated with percent breast water content in all young women aged 15-30, and the associations remained statistically significant after adjustment for height, weight and other covariates. IGF-I was not associated with any MR breast measures. Serum levels of estradiol, progesterone, and testosterone, were not associated with MR breast measures in all young women, or in those aged 20-30, but did show evidence of positive associations with percent water in those aged 15-19 years.
After adjustment for other covariates, interactions of age and serum levels of testosterone (p=0.02) and progesterone (p=0.03) were associated with percent water, and estradiol with total water (p=0.07).
Conclusions
Serum levels of sex hormones were associated with breast tissue composition in young women aged less than 20, while GH and SHBG were associated with breast tissue composition in all young women.
Citation Information: Cancer Prev Res 2008;1(7 Suppl):A123.
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Affiliation(s)
- Lisa Martin
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Inst., Toronto, Ontario, Canada, Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Sofia Chavez
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Inst., Toronto, Ontario, Canada, Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Anoma Gunasekara
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Inst., Toronto, Ontario, Canada, Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Ayesha Salleh
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Inst., Toronto, Ontario, Canada, Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Olga Melnichouk
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Inst., Toronto, Ontario, Canada, Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Martin Yaffe
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Inst., Toronto, Ontario, Canada, Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Salomon Minkin
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Inst., Toronto, Ontario, Canada, Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Michael Bronskill
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Inst., Toronto, Ontario, Canada, Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Norman Boyd
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Inst., Toronto, Ontario, Canada, Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
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Scott CJ, Chavez S, Graham SJ, Black SE. IC‐P3‐214: 2‐D chemical‐shift imaging (CSI) of white matter hyperintensities in Alzheimer's disease – A qualitative analysis. Alzheimers Dement 2008. [DOI: 10.1016/j.jalz.2008.05.159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
| | - Sofia Chavez
- Sunnybrook Health Sciences Centre, Imaging ResearchTorontoONCanada
| | - Simon J. Graham
- Rotman Research Institute, Baycrest Centre for Geriatric CareTorontoONCanada
- Department of Medical BiophysicsUniversity of TorontoTorontoONCanada
| | - Sandra E. Black
- Sunnybrook Health Sciences CentreTorontoONCanada
- University of TorontoTorontoONCanada
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Scott CJ, Chavez S, Graham SJ, Black SE. P2‐076: 2‐D chemical‐shift imaging (CSI) of white matter hyperintensities in Alzheimer's disease: A qualitative analysis. Alzheimers Dement 2008. [DOI: 10.1016/j.jalz.2008.05.1149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
| | - Sofia Chavez
- Sunnybrook Health Sciences Centre, Imaging ResearchTorontoONCanada
| | - Simon J. Graham
- Rotman Research InstituteBaycrest Centre for Geriatric CareTorontoONCanada
- Department of Medical BiophysicsUniversity of TorontoTorontoONCanada
| | - Sandra E. Black
- Sunnybrook Health Sciences CentreTorontoONCanada
- University of TorontoTorontoONCanada
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Arlabosse P, Chavez S, Prevot C. Drying of municipal sewage sludge: from a laboratory scale batch indirect dryer to the paddle dryer. Braz J Chem Eng 2005. [DOI: 10.1590/s0104-66322005000200009] [Citation(s) in RCA: 34] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
| | - S. Chavez
- Ecole des Mines d'Albi Carmaux, France
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Abstract
This paper describes phase maps. A review of the phase unwrapping problem is given. Different structures, in particular fringelines, cutlines, and poles, contained within a phase map are described and their origin and behavior investigated. The problem of phase unwrapping can then be addressed with a better understanding of the source of poles or inconsistencies. This understanding, along with some assumptions about what is being encoded in the phase of a magnetic resonance image, are used to derive a new method for phase unwrapping which relies only on the phase map. The method detects cutlines and distinguishes between noise-induced poles and signal undersampling poles based on the length of the fringelines. The method was shown to be robust to noise and successful in unwrapping challenging clinical cases.
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Affiliation(s)
- Sofia Chavez
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC V6T IZI, Canada
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An L, Xiang QS, Chavez S. A fast implementation of the minimum spanning tree method for phase unwrapping. IEEE Trans Med Imaging 2000; 19:805-808. [PMID: 11055804 DOI: 10.1109/42.876306] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
A new implementation of the minimum spanning tree (MST) phase unwrapping method is presented. The time complexity of the MST method is reduced from O(n2) to O(n log2 n), where n is the number of pixels in the phase map. Typical 256 x 256 phase maps from magnetic resonance imaging can be unwrapped in seconds, compared with tens of minutes with the O(n2) implementation. This makes the pixel-level MST method time efficient and practically attractive. Index Terms-Image processing, magnetic resonance imaging, medical imaging, phase unwrapping.
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