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Dogahe MH, Ramezani S, Reihanian Z, Raminfard S, Feizkhah A, Alijani B, Herfeh SS. Role of brain metabolites during acute phase of mild traumatic brain injury in prognosis of post-concussion syndrome: A 1H-MRS study. Psychiatry Res Neuroimaging 2023; 335:111709. [PMID: 37688998 DOI: 10.1016/j.pscychresns.2023.111709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 06/20/2023] [Accepted: 08/24/2023] [Indexed: 09/11/2023]
Abstract
This study has investigated the potency and accuracy of early magnetic resonance spectroscopy (MRS) to predict post-concussion syndrome (PCS) in adult patients with a single mild traumatic brain injury (mTBI) without abnormality on a routine brain scan. A total of 48 eligible mTBI patients and 24 volunteers in the control group participated in this project. Brain MRS over regions of interest (ROI) and signal stop task (SST) were done within the first 72 hours of TBI onset. After six months, PCS appearance and severity were determined. In non-PCS patients, N-acetyl aspartate (NAA) levels significantly increased in the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC) relative to the control group, however, this increase of NAA levels were recorded in all ROI versus PCS subjects. There were dramatic declines in creatinine (Cr) levels of all ROI and a decrease in choline levels of corpus callosum (CC) in the PCS group versus control and non-PCS ones. NAA and NAA/Cho values in ACC were the main predictors of PCS appearance. The Cho/Cr level in ACC was the first predictor of PCS severity. Predicting accuracy was higher in ACC than in other regions. This study suggested the significance of neuro-markers in ACC for optimal prediction of PCS and rendered a new insight into the biological mechanism of mTBI that underpins PCS.
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Affiliation(s)
| | - Sara Ramezani
- Guilan Road Trauma Research Center, Guilan University of Medical Sciences, Rasht, Iran; Department of Food Science and Nutrition, California State University, Fresno, CA, USA; Neuroscience Research Center, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
| | - Zoheir Reihanian
- Department of Neurosurgery, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran
| | - Samira Raminfard
- Neuroimaging and Analysis Group, Research Center of Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Alireza Feizkhah
- Burn and Regenerative Medicine Research Center, Guilan University of Medical Sciences, Rasht, Iran; Department of Medical Physics, Guilan University of Medical Sciences, Rasht, Iran
| | - Babak Alijani
- Guilan Road Trauma Research Center, Guilan University of Medical Sciences, Rasht, Iran; Department of Neurosurgery, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran
| | - Sina Sedaghat Herfeh
- Neuroscience Research Center, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran
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Gudmundson AT, Koo A, Virovka A, Amirault AL, Soo M, Cho JH, Oeltzschner G, Edden RAE, Stark CEL. Meta-analysis and open-source database for in vivo brain Magnetic Resonance spectroscopy in health and disease. Anal Biochem 2023; 676:115227. [PMID: 37423487 PMCID: PMC10561665 DOI: 10.1016/j.ab.2023.115227] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 06/15/2023] [Accepted: 06/26/2023] [Indexed: 07/11/2023]
Abstract
Proton (1H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo. Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.
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Affiliation(s)
- Aaron T Gudmundson
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Annie Koo
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Anna Virovka
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Alyssa L Amirault
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Madelene Soo
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Jocelyn H Cho
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Craig E L Stark
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA.
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Hyzak KA, Bunger AC, Bogner J, Davis AK, Corrigan JD. Implementing traumatic brain injury screening in behavioral health treatment settings: results of an explanatory sequential mixed-methods investigation. Implement Sci 2023; 18:35. [PMID: 37587532 PMCID: PMC10428542 DOI: 10.1186/s13012-023-01289-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 07/31/2023] [Indexed: 08/18/2023] Open
Abstract
BACKGROUND Traumatic brain injury (TBI) is a complex condition common among individuals treated in behavioral healthcare, but TBI screening has not been adopted in these settings which can affect optimal clinical decision-making. Integrating evidence-based practices that address complex health comorbidities into behavioral healthcare settings remains understudied in implementation science, limited by few studies using theory-driven hypotheses to disentangle relationships between proximal and medial indicators on distal implementation outcomes. Grounded in the Theory of Planned Behavior, we examined providers' attitudes, perceived behavioral control (PBC), subjective norms, and intentions to adopt The Ohio State University TBI Identification Method (OSU TBI-ID) in behavioral healthcare settings. METHODS We used an explanatory sequential mixed-methods design. In Phase I, 215 providers from 25 organizations in the USA completed training introducing the OSU TBI-ID, followed by a survey assessing attitudes, PBC, norms, and intentions to screen for TBI. After 1 month, providers completed another survey assessing the number of TBI screens conducted. Data were analyzed using structural equation modeling (SEM) with logistic regressions. In Phase II, 20 providers were purposively selected for semi-structured interviews to expand on SEM results. Qualitative data were analyzed using thematic analysis, integrated with quantitative results, and combined into joint displays. RESULTS Only 25% (55/215) of providers adopted TBI screening, which was driven by motivations to trial the intervention. Providers who reported more favorable attitudes (OR: 0.67, p < .001) and greater subjective norms (OR: 0.12, p < .001) toward TBI screening demonstrated increased odds of intention to screen, which resulted in greater TBI screening adoption (OR: 0.30; p < .01). PBC did not affect intentions or adoption. Providers explained that although TBI screening can improve diagnostic and clinical decision-making, they discussed that additional training, leadership engagement, and state-level mandates are needed to increase the widespread, systematic uptake of TBI screening. CONCLUSIONS This study advances implementation science by using theory-driven hypothesis testing to disentangle proximal and medial indicators at the provider level on TBI screening adoption. Our mixed-methods approach added in-depth contextualization and illuminated additional multilevel determinants affecting intervention adoption, which guides a more precise selection of implementation strategies.
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Affiliation(s)
- Kathryn A Hyzak
- Department of Physical Medicine and Rehabilitation, The Ohio State University College of Medicine, Columbus, OH, 43210-1234, USA.
| | - Alicia C Bunger
- College of Social Work, The Ohio State University, Columbus, OH, USA
| | - Jennifer Bogner
- Department of Physical Medicine and Rehabilitation, The Ohio State University College of Medicine, Columbus, OH, 43210-1234, USA
| | - Alan K Davis
- College of Social Work, The Ohio State University, Columbus, OH, USA
- Department of Psychiatry and Behavioral Sciences, Center for Psychedelic and Consciousness Research, Johns Hopkins University Baltimore, Baltimore, MD, USA
- Department of Psychiatry, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - John D Corrigan
- Department of Physical Medicine and Rehabilitation, The Ohio State University College of Medicine, Columbus, OH, 43210-1234, USA
- Ohio Valley Center for Brain Injury Prevention and Rehabilitation, The Ohio State University Wexner Medical Center, Columbus, OH, USA
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Gudmundson AT, Koo A, Virovka A, Amirault AL, Soo M, Cho JH, Oeltzschner G, Edden RA, Stark C. Meta-analysis and Open-source Database for In Vivo Brain Magnetic Resonance Spectroscopy in Health and Disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.10.528046. [PMID: 37205343 PMCID: PMC10187197 DOI: 10.1101/2023.02.10.528046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Proton ( 1 H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo . Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T 2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.
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Affiliation(s)
- Aaron T. Gudmundson
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
| | - Annie Koo
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA
| | - Anna Virovka
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA
| | - Alyssa L. Amirault
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA
| | - Madelene Soo
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA
| | - Jocelyn H. Cho
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
| | - Richard A.E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
| | - Craig Stark
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA
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Li B, Zhang D, Verkhratsky A. Astrocytes in Post-traumatic Stress Disorder. Neurosci Bull 2022; 38:953-965. [PMID: 35349095 PMCID: PMC8960712 DOI: 10.1007/s12264-022-00845-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 01/07/2022] [Indexed: 01/15/2023] Open
Abstract
Although posttraumatic stress disorder (PTSD) is on the rise, traumatic events and their consequences are often hidden or minimized by patients for reasons linked to PTSD itself. Traumatic experiences can be broadly classified into mental stress (MS) and traumatic brain injury (TBI), but the cellular mechanisms of MS- or TBI-induced PTSD remain unknown. Recent evidence has shown that the morphological remodeling of astrocytes accompanies and arguably contributes to fearful memories and stress-related disorders. In this review, we summarize the roles of astrocytes in the pathogenesis of MS-PTSD and TBI-PTSD. Astrocytes synthesize and secrete neurotrophic, pro- and anti-inflammatory factors and regulate the microenvironment of the nervous tissue through metabolic pathways, ionostatic control, and homeostatic clearance of neurotransmitters. Stress or trauma-associated impairment of these vital astrocytic functions contribute to the pathophysiological evolution of PTSD and may present therapeutic targets.
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Affiliation(s)
- Baoman Li
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, 110122, China
| | - Dianjun Zhang
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, 110122, China
| | - Alexei Verkhratsky
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, 110122, China.
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PT, UK.
- Department of Stem Cell Biology, State Research Institute Centre for Innovative Medicine, 01102, Vilnius, Lithuania.
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Lin JC, Mueller C, Campbell KA, Thannickal HH, Daredia AF, Sheriff S, Maudsley AA, Brunner RC, Younger JW. Investigating whole-brain metabolite abnormalities in the chronic stages of moderate or severe traumatic brain injury. PM R 2021; 14:472-485. [PMID: 33930238 DOI: 10.1002/pmrj.12623] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 04/18/2021] [Accepted: 04/19/2021] [Indexed: 12/30/2022]
Abstract
BACKGROUND Evidence suggests that neurometabolic abnormalities can persist after traumatic brain injury (TBI) and drive clinical symptoms such as fatigue and cognitive disruption. Magnetic resonance spectroscopy has been used to investigate metabolite abnormalities following TBI, but few studies have obtained data beyond the subacute stage or over large brain regions. OBJECTIVE To measure whole-brain metabolites in chronic stages of TBI. DESIGN Observational study. SETTING University. PARTICIPANTS Eleven men with a moderate or severe TBI more than 12 months prior and 10 age-matched healthy controls completed whole-brain spectroscopic imaging. MAIN MEASURES Ratios of N-acetylaspartate (NAA), choline (CHO), and myo-inositol (MI) to creatine (CR) were measured in whole-brain gray and white matter as well as 64 brain regions of interest. Arterial spin labeling (ASL) data were also collected to investigate whether metabolite abnormalities were accompanied by differences in cerebral perfusion. RESULTS There were no differences in metabolite ratios within whole-brain gray and white matter regions of interest (ROIs). Linear regression showed lower NAA/CR in the white matter of the left occipital lobe but higher NAA/CR in the gray matter of the left parietal lobe. Metabolite abnormalities were observed in several brain regions in the TBI group including the corpus callosum, putamen, and posterior cingulate. However, none of the findings survived correction for multiple comparison. There were no differences in cerebral blood flow between patients and controls. CONCLUSION Higher MI/CR may indicate ongoing gliosis, and it has been suggested that low CHO/CR at chronic time points may indicate cell death or lack of healthy turnover and repair. However, with the small sample size of this study, we caution against the overinterpretation of our results. None of the findings within ROIs survived correction for multiple comparison. Thus, they may be considered possible avenues for future research in this area.
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Affiliation(s)
- Joanne C Lin
- Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Christina Mueller
- Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Kelsey A Campbell
- Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | | | - Altamish F Daredia
- Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Sulaiman Sheriff
- Department of Radiology, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Andrew A Maudsley
- Department of Radiology, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Robert C Brunner
- Department of Physical Medicine and Rehabilitation, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Jarred W Younger
- Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, USA
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