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Tayebi M, Kwon E, Maller J, McGeown J, Scadeng M, Qiao M, Wang A, Nielsen P, Fernandez J, Holdsworth S, Shim V. Integration of diffusion tensor imaging parameters with mesh morphing for in-depth analysis of brain white matter fibre tracts. Brain Commun 2024; 6:fcae027. [PMID: 38638147 PMCID: PMC11024816 DOI: 10.1093/braincomms/fcae027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 10/06/2023] [Accepted: 02/07/2024] [Indexed: 04/20/2024] Open
Abstract
Averaging is commonly used for data reduction/aggregation to analyse high-dimensional MRI data, but this often leads to information loss. To address this issue, we developed a novel technique that integrates diffusion tensor metrics along the whole volume of the fibre bundle using a 3D mesh-morphing technique coupled with principal component analysis for delineating case and control groups. Brain diffusion tensor MRI scans of high school rugby union players (n = 30, age 16-18) were acquired on a 3 T MRI before and after the sports season. A non-contact sport athlete cohort with matching demographics (n = 12) was also scanned. The utility of the new method in detecting differences in diffusion tensor metrics of the right corticospinal tract between contact and non-contact sport athletes was explored. The first step was to run automated tractography on each subject's native space. A template model of the right corticospinal tract was generated and morphed into each subject's native shape and space, matching individual geometry and diffusion metric distributions with minimal information loss. The common dimension of the 20 480 diffusion metrics allowed further data aggregation using principal component analysis to cluster the case and control groups as well as visualization of diffusion metric statistics (mean, ±2 SD). Our approach of analysing the whole volume of white matter tracts led to a clear delineation between the rugby and control cohort, which was not possible with the traditional averaging method. Moreover, our approach accounts for the individual subject's variations in diffusion tensor metrics to visualize group differences in quantitative MR data. This approach may benefit future prediction models based on other quantitative MRI methods.
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Affiliation(s)
- Maryam Tayebi
- Auckland Bioengineering Institute, The University of Auckland, Auckland, 1010, New Zealand
- Mātai Medical Research Institute, Gisborne, 4010, New Zealand
| | - Eryn Kwon
- Auckland Bioengineering Institute, The University of Auckland, Auckland, 1010, New Zealand
- Mātai Medical Research Institute, Gisborne, 4010, New Zealand
| | | | - Josh McGeown
- Mātai Medical Research Institute, Gisborne, 4010, New Zealand
| | - Miriam Scadeng
- Mātai Medical Research Institute, Gisborne, 4010, New Zealand
- Faculty of Medical and Health Sciences, The University of Auckland, Auckland, 1023, New Zealand
| | - Miao Qiao
- Department of Computer Science, The University of Auckland, Auckland, 1010, New Zealand
| | - Alan Wang
- Auckland Bioengineering Institute, The University of Auckland, Auckland, 1010, New Zealand
- Faculty of Medical and Health Sciences, The University of Auckland, Auckland, 1023, New Zealand
| | - Poul Nielsen
- Auckland Bioengineering Institute, The University of Auckland, Auckland, 1010, New Zealand
- Department of Engineering Science, The University of Auckland, Auckland, 1010, New Zealand
| | - Justin Fernandez
- Auckland Bioengineering Institute, The University of Auckland, Auckland, 1010, New Zealand
- Mātai Medical Research Institute, Gisborne, 4010, New Zealand
- Department of Engineering Science, The University of Auckland, Auckland, 1010, New Zealand
| | - Samantha Holdsworth
- Mātai Medical Research Institute, Gisborne, 4010, New Zealand
- Faculty of Medical and Health Sciences, The University of Auckland, Auckland, 1023, New Zealand
| | - Vickie Shim
- Auckland Bioengineering Institute, The University of Auckland, Auckland, 1010, New Zealand
- Mātai Medical Research Institute, Gisborne, 4010, New Zealand
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Davidson TL, Stevenson RJ. Vulnerability of the Hippocampus to Insults: Links to Blood-Brain Barrier Dysfunction. Int J Mol Sci 2024; 25:1991. [PMID: 38396670 PMCID: PMC10888241 DOI: 10.3390/ijms25041991] [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: 01/03/2024] [Revised: 01/25/2024] [Accepted: 01/29/2024] [Indexed: 02/25/2024] Open
Abstract
The hippocampus is a critical brain substrate for learning and memory; events that harm the hippocampus can seriously impair mental and behavioral functioning. Hippocampal pathophysiologies have been identified as potential causes and effects of a remarkably diverse array of medical diseases, psychological disorders, and environmental sources of damage. It may be that the hippocampus is more vulnerable than other brain areas to insults that are related to these conditions. One purpose of this review is to assess the vulnerability of the hippocampus to the most prevalent types of insults in multiple biomedical domains (i.e., neuroactive pathogens, neurotoxins, neurological conditions, trauma, aging, neurodegenerative disease, acquired brain injury, mental health conditions, endocrine disorders, developmental disabilities, nutrition) and to evaluate whether these insults affect the hippocampus first and more prominently compared to other brain loci. A second purpose is to consider the role of hippocampal blood-brain barrier (BBB) breakdown in either causing or worsening the harmful effects of each insult. Recent research suggests that the hippocampal BBB is more fragile compared to other brain areas and may also be more prone to the disruption of the transport mechanisms that act to maintain the internal milieu. Moreover, a compromised BBB could be a factor that is common to many different types of insults. Our analysis indicates that the hippocampus is more vulnerable to insults compared to other parts of the brain, and that developing interventions that protect the hippocampal BBB may help to prevent or ameliorate the harmful effects of many insults on memory and cognition.
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Affiliation(s)
- Terry L. Davidson
- Department of Neuroscience, Center for Neuroscience and Behavior, American University, 4400 Massachusetts Avenue, NW, Washington, DC 20016, USA
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Everson CA, Szabo A, Plyer C, Hammeke TA, Stemper BD, Budde MD. Sleep loss, caffeine, sleep aids and sedation modify brain abnormalities of mild traumatic brain injury. Exp Neurol 2024; 372:114620. [PMID: 38029810 DOI: 10.1016/j.expneurol.2023.114620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 11/06/2023] [Accepted: 11/21/2023] [Indexed: 12/01/2023]
Abstract
Little evidence exists about how mild traumatic brain injury (mTBI) is affected by commonly encountered exposures of sleep loss, sleep aids, and caffeine that might be potential therapeutic opportunities. In addition, while propofol sedation is administered in severe TBI, its potential utility in mild TBI is unclear. Each of these exposures is known to have pronounced effects on cerebral metabolism and blood flow and neurochemistry. We hypothesized that they each interact with cerebral metabolic dynamics post-injury and change the subclinical characteristics of mTBI. MTBI in rats was produced by head rotational acceleration injury that mimics the biomechanics of human mTBI. Three mTBIs spaced 48 h apart were used to increase the likelihood that vulnerabilities induced by repeated mTBI would be manifested without clinically relevant structural damage. After the third mTBI, rats were immediately sleep deprived or administered caffeine or suvorexant (an orexin antagonist and sleep aid) for the next 24 h or administered propofol for 5 h. Resting state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) were performed 24 h after the third mTBI and again after 30 days to determine changes to the brain mTBI phenotype. Multi-modal analyses on brain regions of interest included measures of functional connectivity and regional homogeneity from rs-fMRI, and mean diffusivity (MD) and fractional anisotropy (FA) from DTI. Each intervention changed the mTBI profile of subclinical effects that presumably underlie healing, compensation, damage, and plasticity. Sleep loss during the acute post-injury period resulted in dramatic changes to functional connectivity. Caffeine, propofol sedation and suvorexant were especially noteworthy for differential effects on microstructure in gray and white matter regions after mTBI. The present results indicate that commonplace exposures and short-term sedation alter the subclinical manifestations of repeated mTBI and therefore likely play roles in symptomatology and vulnerability to damage by repeated mTBI.
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Affiliation(s)
- Carol A Everson
- Department of Medicine (Endocrinology and Molecular Medicine) and Cell Biology, Neurobiology & Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA.
| | - Aniko Szabo
- Division of Biostatistics, Institute for Health & Equity, Medical College of Wisconsin, Milwaukee, WI, USA.
| | - Cade Plyer
- Neurology Residency Program, Department of Neurology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
| | - Thomas A Hammeke
- Department of Psychiatry and Behavioral Medicine, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Brian D Stemper
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA; Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI, USA; Neuroscience Research, Zablocki Veterans Affairs Medical Center, Milwaukee, WI, USA.
| | - Mathew D Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA.
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McNerney MW, Gurkoff GG, Beard C, Berryhill ME. The Rehabilitation Potential of Neurostimulation for Mild Traumatic Brain Injury in Animal and Human Studies. Brain Sci 2023; 13:1402. [PMID: 37891771 PMCID: PMC10605899 DOI: 10.3390/brainsci13101402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/25/2023] [Accepted: 09/28/2023] [Indexed: 10/29/2023] Open
Abstract
Neurostimulation carries high therapeutic potential, accompanied by an excellent safety profile. In this review, we argue that an arena in which these tools could provide breakthrough benefits is traumatic brain injury (TBI). TBI is a major health problem worldwide, with the majority of cases identified as mild TBI (mTBI). MTBI is of concern because it is a modifiable risk factor for dementia. A major challenge in studying mTBI is its inherent heterogeneity across a large feature space (e.g., etiology, age of injury, sex, treatment, initial health status, etc.). Parallel lines of research in human and rodent mTBI can be collated to take advantage of the full suite of neuroscience tools, from neuroimaging (electroencephalography: EEG; functional magnetic resonance imaging: fMRI; diffusion tensor imaging: DTI) to biochemical assays. Despite these attractive components and the need for effective treatments, there are at least two major challenges to implementation. First, there is insufficient understanding of how neurostimulation alters neural mechanisms. Second, there is insufficient understanding of how mTBI alters neural function. The goal of this review is to assemble interrelated but disparate areas of research to identify important gaps in knowledge impeding the implementation of neurostimulation.
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Affiliation(s)
- M. Windy McNerney
- Mental Illness Research Education and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA; (M.W.M.); (C.B.)
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Gene G. Gurkoff
- Department of Neurological Surgery, and Center for Neuroscience, University of California, Davis, Sacramento, CA 95817, USA;
- Department of Veterans Affairs, VA Northern California Health Care System, Martinez, CA 94553, USA
| | - Charlotte Beard
- Mental Illness Research Education and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA; (M.W.M.); (C.B.)
- Program in Neuroscience and Behavioral Biology, Emory University, Atlanta, GA 30322, USA
| | - Marian E. Berryhill
- Programs in Cognitive and Brain Sciences, and Integrative Neuroscience, Department of Psychology, University of Nevada, Reno, NV 89557, USA
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Brennan DJ, Duda J, Ware JB, Whyte J, Choi JY, Gugger J, Focht K, Walter AE, Bushnik T, Gee JC, Diaz‐Arrastia R, Kim JJ. Spatiotemporal profile of atrophy in the first year following moderate-severe traumatic brain injury. Hum Brain Mapp 2023; 44:4692-4709. [PMID: 37399336 PMCID: PMC10400790 DOI: 10.1002/hbm.26410] [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: 12/12/2022] [Revised: 06/04/2023] [Accepted: 06/12/2023] [Indexed: 07/05/2023] Open
Abstract
Traumatic brain injury (TBI) triggers progressive neurodegeneration resulting in brain atrophy that continues months-to-years following injury. However, a comprehensive characterization of the spatial and temporal evolution of TBI-related brain atrophy remains incomplete. Utilizing a sensitive and unbiased morphometry analysis pipeline optimized for detecting longitudinal changes, we analyzed a sample consisting of 37 individuals with moderate-severe TBI who had primarily high-velocity and high-impact injury mechanisms. They were scanned up to three times during the first year after injury (3 months, 6 months, and 12 months post-injury) and compared with 33 demographically matched controls who were scanned once. Individuals with TBI already showed cortical thinning in frontal and temporal regions and reduced volume in the bilateral thalami at 3 months post-injury. Longitudinally, only a subset of cortical regions in the parietal and occipital lobes showed continued atrophy from 3 to 12 months post-injury. Additionally, cortical white matter volume and nearly all deep gray matter structures exhibited progressive atrophy over this period. Finally, we found that disproportionate atrophy of cortex along sulci relative to gyri, an emerging morphometric marker of chronic TBI, was present as early as 3 month post-injury. In parallel, neurocognitive functioning largely recovered during this period despite this pervasive atrophy. Our findings demonstrate msTBI results in characteristic progressive neurodegeneration patterns that are divergent across regions and scale with the severity of injury. Future clinical research using atrophy during the first year of TBI as a biomarker of neurodegeneration should consider the spatiotemporal profile of atrophy described in this study.
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Affiliation(s)
- Daniel J. Brennan
- CUNY Neuroscience Collaborative, The Graduate CenterCity University of New YorkNew YorkNew YorkUnited States
- Department of Molecular, Cellular, and Biomedical SciencesCUNY School of Medicine, The City College of New YorkNew YorkNew YorkUnited States
| | - Jeffrey Duda
- Department of RadiologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUnited States
- Penn Image Computing and Science LaboratoryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUnited States
| | - Jeffrey B. Ware
- Department of RadiologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUnited States
| | - John Whyte
- Moss Rehabilitation Research Institute, Einstein Healthcare NetworkElkins ParkPennsylvaniaUnited States
| | - Joon Yul Choi
- Department of Molecular, Cellular, and Biomedical SciencesCUNY School of Medicine, The City College of New YorkNew YorkNew YorkUnited States
- Department of Biomedical EngineeringYonsei UniversityWonjuRepublic of Korea
| | - James Gugger
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUnited States
| | - Kristen Focht
- Widener University School for Graduate Clinical PsychologyChesterPennsylvaniaUnited States
| | - Alexa E. Walter
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUnited States
| | - Tamara Bushnik
- NYU Grossman School of MedicineNew YorkNew YorkUnited States
| | - James C. Gee
- Department of RadiologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUnited States
- Penn Image Computing and Science LaboratoryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUnited States
| | - Ramon Diaz‐Arrastia
- Department of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUnited States
| | - Junghoon J. Kim
- CUNY Neuroscience Collaborative, The Graduate CenterCity University of New YorkNew YorkNew YorkUnited States
- Department of Molecular, Cellular, and Biomedical SciencesCUNY School of Medicine, The City College of New YorkNew YorkNew YorkUnited States
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6
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de Souza N, Esopenko C, Jia Y, Parrott JS, Merkley T, Dennis E, Hillary F, Velez C, Cooper D, Kennedy J, Lewis J, York G, Menefee D, McCauley S, Bowles AO, Wilde E, Tate DF. Discriminating Mild Traumatic Brain Injury and Posttraumatic Stress Disorder Using Latent Neuroimaging and Neuropsychological Profiles in Active-Duty Military Service Members. J Head Trauma Rehabil 2023; 38:E254-E266. [PMID: 36602276 PMCID: PMC10264548 DOI: 10.1097/htr.0000000000000848] [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] [Indexed: 01/06/2023]
Abstract
OBJECTIVE Mild traumatic brain injury (mTBI) and posttraumatic stress disorder (PTSD) commonly occur among military Service Members and Veterans and have heterogenous, but also overlapping symptom presentations, which often complicate the diagnoses of underlying impairments and development of effective treatment plans. Thus, we sought to examine whether the combination of whole brain gray matter (GM) and white matter (WM) structural measures with neuropsychological performance can aid in the classification of military personnel with mTBI and PTSD. METHODS Active-Duty US Service Members ( n = 156; 87.8% male) with a history of mTBI, PTSD, combined mTBI+PTSD, or orthopedic injury completed a neuropsychological battery and T1- and diffusion-weighted structural neuroimaging. Cortical, subcortical, ventricular, and WM volumes and whole brain fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were calculated. Latent profile analyses were performed to determine how the GM and WM indicators, together with neuropsychological indicators, classified individuals. RESULTS For both GM and WM, respectively, a 4-profile model was the best fit. The GM model identified greater ventricular volumes in Service Members with cognitive symptoms, including those with a diagnosis of mTBI, either alone or with PTSD. The WM model identified reduced FA and elevated RD in those with psychological symptoms, including those with PTSD or mTBI and comorbid PTSD. However, contrary to expectation, a global neural signature unique to those with comorbid mTBI and PTSD was not identified. CONCLUSIONS The findings demonstrate that neuropsychological performance alone is more robust in differentiating Active-Duty Service Members with mTBI and PTSD, whereas global neuroimaging measures do not reliably differentiate between these groups.
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Affiliation(s)
- N.L. de Souza
- School of Graduate Studies, Biomedical Sciences, Rutgers Biomedical and Health Sciences, Newark, NJ, USA
| | - C. Esopenko
- Department of Rehabilitation & Movement Sciences, School of Health Professions, Rutgers Biomedical and Health Sciences, Newark, NJ, USA
| | - Y. Jia
- Department of Interdisciplinary Studies, School of Health Professions, Rutgers Biomedical and Health Sciences, Newark, NJ, USA
| | - J. S. Parrott
- Department of Interdisciplinary Studies, School of Health Professions, Rutgers Biomedical and Health Sciences, Newark, NJ, USA
| | - T.L. Merkley
- Department of Psychology & Neuroscience Center, Brigham Young University, Provo, UT, USA
- Traumatic Brain Injury and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - E.L. Dennis
- Traumatic Brain Injury and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT
| | - F.G. Hillary
- Department of Psychology, Pennsylvania State University, University Park, PA 16802, United States
- Social Life and Engineering Sciences Imaging Center, University Park, PA 16802, United States
| | - C. Velez
- Traumatic Brain Injury and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - D.B. Cooper
- San Antonio VA Polytrauma Rehabilitation Center, San Antonio, TX
- Departments of Rehabilitation Medicine and Psychiatry, UT Health San Antonio, TX
| | - J. Kennedy
- General Dynamics Information Technology (GDIT) contractor for the Traumatic Brain Injury Center of Excellence (TBICoE), Neurology Service, Department of Medicine, Brooke Army Medical Center, Joint Base San Antonio, Fort Sam Houston, TX, USA
| | - J. Lewis
- Neurology Clinic, Wright Patterson Air Force Base, Wright Patterson AFB, Ohio
| | - G. York
- Alaska Radiology Associates, Anchorage, AK
| | - D.S. Menefee
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
- The Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX USA
| | - S.R. McCauley
- Department of Neurology, Baylor College of Medicine, Houston, TX USA
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX USA
- Department of Pediatrics, Baylor College of Medicine, Houston, TX USA
| | - A. O. Bowles
- Brain Injury Rehabilitation Service, Department of Rehabilitation Medicine, Brooke Army Medical Center, Joint Base San Antonio, Fort Sam Houston, TX, US
| | - E.A. Wilde
- Traumatic Brain Injury and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX USA
| | - D. F. Tate
- Traumatic Brain Injury and Concussion Center, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT
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Wang X, Wang Y, He L. An intelligent data analysis-based medical management method for lower limb health of football athletes. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2023; 20:14005-14022. [PMID: 37679121 DOI: 10.3934/mbe.2023624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/09/2023]
Abstract
With increasingly mature commercial operations, football has become the most popular sport in the world. As the main body of football, athletes are prone to injury due to an increasing degree of competition intensity. Their health determines the length of these athletes careers, especially regarding the lower limbs that are mainly used. Therefore, the smart visualization approaches that can realize such function are in urgent demand in the area of sports healthcare. Benefitted by the strong ability of perception and analysis, a convolutional neural network (CNN) is utilized to construct an intelligent data analysis-based medical management method for the lower limb health of football athletes. First, the CNN is formulated as the main backbone, and its parameters are optimized for multiple rounds during the training stage. Then, a statistical analysis software named SPSS is introduced to assess the effect mechanism of different postures on lower limbs. Some experiments are carried out on simulative data to evaluate the proposed method, and results show a good performance of the proposed method.
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Affiliation(s)
- Xiang Wang
- Department of Physical Education, Gansu University of Political Science and Law, Lanzhou 730030, China
| | - Yongcheng Wang
- Volleyball Teaching and Research Department, Xi'an Physical Education University, Xi'an 710000, China
| | - Limin He
- Department of Physical Education, Lanzhou University, Lanzhou 730000, China
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8
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Ware JB, Sandsmark DK. Imaging Approach to Concussion. Neuroimaging Clin N Am 2023; 33:261-269. [PMID: 36965944 DOI: 10.1016/j.nic.2023.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/20/2023]
Abstract
The acute and long-term neurobiological sequelae of concussion (mild traumatic brain injury [mTBI]) and sub-concussive head trauma have become increasingly apparent in recent decades in part due to neuroimaging research. Although imaging has an established role in the clinical management of mTBI for the identification of intracranial lesions warranting urgent interventions, MR imaging is increasingly employed for the detection of post-traumatic sequelae which carry important prognostic significance. As neuroimaging research continues to elucidate the pathophysiology of TBI underlying prolonged recovery and the development of persistent post-concussive symptoms, there is a strong motivation to translate these techniques into clinical use for improved diagnosis and therapeutic monitoring.
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Affiliation(s)
- Jeffrey B Ware
- Department of Radiology, Neuroradiology Division, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA.
| | - Danielle K Sandsmark
- Department of Neurology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
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9
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Gimbel SI, Wang CC, Hungerford L, Twamley EW, Ettenhofer ML. Associations of mTBI and post-traumatic stress to amygdala structure and functional connectivity in military Service Members. FRONTIERS IN NEUROIMAGING 2023; 2:1129446. [PMID: 37554633 PMCID: PMC10406312 DOI: 10.3389/fnimg.2023.1129446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 02/07/2023] [Indexed: 08/10/2023]
Abstract
INTRODUCTION Traumatic brain injury (TBI) is one of the highest public health priorities, especially among military personnel where comorbidity with post-traumatic stress symptoms and resulting consequences is high. Brain injury and post-traumatic stress symptoms are both characterized by dysfunctional brain networks, with the amygdala specifically implicated as a region with both structural and functional abnormalities. METHODS This study examined the structural volumetrics and resting state functional connectivity of 68 Active Duty Service Members with or without chronic mild TBI (mTBI) and comorbid symptoms of Post-Traumatic Stress (PTS). RESULTS AND DISCUSSION Structural analysis of the amygdala revealed no significant differences in volume between mTBI and healthy comparison participants with and without post-traumatic stress symptoms. Resting state functional connectivity with bilateral amygdala revealed decreased anterior network connectivity and increased posterior network connectivity in the mTBI group compared to the healthy comparison group. Within the mTBI group, there were significant regions of correlation with amygdala that were modulated by PTS severity, including networks implicated in emotional processing and executive functioning. An examination of a priori regions of amygdala connectivity in the default mode network, task positive network, and subcortical structures showed interacting influences of TBI and PTS, only between right amygdala and right putamen. These results suggest that mTBI and PTS are associated with hypo-frontal and hyper-posterior amygdala connectivity. Additionally, comorbidity of these conditions appears to compound these neural activity patterns. PTS in mTBI may change neural resource recruitment for information processing between the amygdala and other brain regions and networks, not only during emotional processing, but also at rest.
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Affiliation(s)
- Sarah I. Gimbel
- Traumatic Brain Injury Center of Excellence, Silver Spring, MD, United States
- Traumatic Brain Injury Clinic, Naval Medical Center San Diego, San Diego, CA, United States
- General Dynamics Information Technology, Falls Church, VA, United States
| | - Cailynn C. Wang
- Department of Psychology, University of California, San Diego, San Diego, CA, United States
| | - Lars Hungerford
- Traumatic Brain Injury Center of Excellence, Silver Spring, MD, United States
- Traumatic Brain Injury Clinic, Naval Medical Center San Diego, San Diego, CA, United States
- General Dynamics Information Technology, Falls Church, VA, United States
| | - Elizabeth W. Twamley
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, United States
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
| | - Mark L. Ettenhofer
- Traumatic Brain Injury Center of Excellence, Silver Spring, MD, United States
- Traumatic Brain Injury Clinic, Naval Medical Center San Diego, San Diego, CA, United States
- General Dynamics Information Technology, Falls Church, VA, United States
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
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10
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Stein MB, Jain S, Parodi L, Choi KW, Maihofer AX, Nelson LD, Mukherjee P, Sun X, He F, Okonkwo DO, Giacino JT, Korley FK, Vassar MJ, Robertson CS, McCrea MA, Temkin N, Markowitz AJ, Diaz-Arrastia R, Rosand J, Manley GT, Duhaime AC, Ferguson AR, Gopinath S, Grandhi R, Madden C, Merchant R, Schnyer D, Taylor SR, Yue JK, Zafonte R. Polygenic risk for mental disorders as predictors of posttraumatic stress disorder after mild traumatic brain injury. Transl Psychiatry 2023; 13:24. [PMID: 36693822 PMCID: PMC9873804 DOI: 10.1038/s41398-023-02313-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 01/03/2023] [Accepted: 01/06/2023] [Indexed: 01/26/2023] Open
Abstract
Many patients with mild traumatic brain injury (mTBI) are at risk for mental health problems such as posttraumatic stress disorder (PTSD). The objective of this study was to determine whether the polygenic risk for PTSD (or for related mental health disorders or traits including major depressive disorder [MDD] and neuroticism [NEU]) was associated with an increased likelihood of PTSD in the aftermath of mTBI. We used data from individuals of European ancestry with mTBI enrolled in TRACK-TBI (n = 714), a prospective longitudinal study of level 1 trauma center patients. One hundred and sixteen mTBI patients (16.3%) had probable PTSD (PCL-5 score ≥33) at 6 months post-injury. We used summary statistics from recent GWAS studies of PTSD, MDD, and NEU to generate polygenic risk scores (PRS) for individuals in our sample. A multivariable model that included age, sex, pre-injury history of mental disorder, and cause of injury explained 7% of the variance in the PTSD outcome; the addition of the PTSD-PRS (and five ancestral principal components) significantly increased the variance explained to 11%. The adjusted odds of PTSD in the uppermost PTSD-PRS quintile was nearly four times higher (aOR = 3.71, 95% CI 1.80-7.65) than in the lowest PTSD-PRS quintile. There was no evidence of a statistically significant interaction between PTSD-PRS and prior history of mental disorder, indicating that PTSD-PRS had similar predictive utility among those with and without pre-injury psychiatric illness. When added to the model, neither MDD-PRS nor NEU-PRS were significantly associated with the PTSD outcome. These findings show that the risk for PTSD in the context of mTBI is, in part, genetically influenced. They also raise the possibility that an individual's PRS could be clinically actionable if used-possibly with other non-genetic predictors-to signal the need for enhanced follow-up and early intervention; this precision medicine approach needs to be prospectively studied.
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Affiliation(s)
- Murray B. Stein
- grid.266100.30000 0001 2107 4242Department of Psychiatry, University of California, San Diego, La Jolla, CA USA ,grid.266100.30000 0001 2107 4242School of Public Health, University of California, San Diego, La Jolla, CA USA ,grid.410371.00000 0004 0419 2708VA San Diego Healthcare System, San Diego, CA USA
| | - Sonia Jain
- grid.266100.30000 0001 2107 4242Biostatistics Research Center, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA USA
| | - Livia Parodi
- grid.32224.350000 0004 0386 9924Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA USA ,grid.32224.350000 0004 0386 9924McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Karmel W. Choi
- grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Adam X. Maihofer
- grid.266100.30000 0001 2107 4242Department of Psychiatry, University of California, San Diego, La Jolla, CA USA
| | - Lindsay D. Nelson
- grid.30760.320000 0001 2111 8460Departments of Neurosurgery and Neurology, Medical College of Wisconsin, Milwaukee, WI USA
| | - Pratik Mukherjee
- grid.266102.10000 0001 2297 6811Department of Radiology & Biomedical Imaging, UCSF, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Bioengineering & Therapeutic Sciences, UCSF, San Francisco, CA USA
| | - Xiaoying Sun
- grid.266100.30000 0001 2107 4242Biostatistics Research Center, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA USA
| | - Feng He
- grid.266100.30000 0001 2107 4242Biostatistics Research Center, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA USA
| | - David O. Okonkwo
- grid.412689.00000 0001 0650 7433Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA USA
| | - Joseph T. Giacino
- grid.38142.3c000000041936754XDepartment of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA USA ,grid.416228.b0000 0004 0451 8771Spaulding Rehabilitation Hospital, Charlestown, MA USA
| | - Frederick K. Korley
- grid.214458.e0000000086837370Department of Emergency Medicine, University of Michigan, Ann Arbor, MI USA
| | - Mary J. Vassar
- grid.416732.50000 0001 2348 2960Brain and Spinal Cord Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Neurological Surgery, UCSF, San Francisco, CA USA
| | - Claudia S. Robertson
- grid.39382.330000 0001 2160 926XDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX USA
| | - Michael A. McCrea
- grid.30760.320000 0001 2111 8460Departments of Neurosurgery and Neurology, Medical College of Wisconsin, Milwaukee, WI USA
| | - Nancy Temkin
- grid.34477.330000000122986657Departments of Neurological Surgery and Biostatistics, University of Washington, Seattle, WA USA
| | - Amy J. Markowitz
- grid.416732.50000 0001 2348 2960Brain and Spinal Cord Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA USA
| | - Ramon Diaz-Arrastia
- grid.25879.310000 0004 1936 8972Department of Neurology, University of Pennsylvania, Philadelphia, PA USA
| | - Jonathan Rosand
- grid.32224.350000 0004 0386 9924Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA USA ,grid.32224.350000 0004 0386 9924McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA USA ,grid.66859.340000 0004 0546 1623Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Geoffrey T. Manley
- grid.416732.50000 0001 2348 2960Brain and Spinal Cord Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Neurological Surgery, UCSF, San Francisco, CA USA
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11
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Du H, Yang B, Wang H, Zeng Y, Xin J, Li X. The non-linear correlation between the volume of cerebral white matter lesions and incidence of bipolar disorder: A secondary analysis of data from a cross-sectional study. Front Psychiatry 2023; 14:1149663. [PMID: 37009125 PMCID: PMC10061585 DOI: 10.3389/fpsyt.2023.1149663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Accepted: 02/21/2023] [Indexed: 04/04/2023] Open
Abstract
Cerebral white matter lesions (WML) are major risk factors for bipolar disorder (BD). However, studies on the association between cerebral WML volume and BD risk are limited. This study aimed to investigate the relationship between cerebral WML volume and BD incidence. This is a secondary retrospective analysis of patients (N = 146, 72 males, 74 females, mean age = 41.77 years) who have previously undergone magnetic resonance imaging examinations. Information was obtained from the Dryad database. Univariate analysis, piecewise linear regression model, and multivariable logistic regression model were used for statistical analysis. A non-linear relationship was recognized between the cerebral WML volume and BD incidence, in which the inflection point of the WML volume was 6,200 mm3. The effect sizes and confidence intervals on the left and right sides of the emphasis point were 1.0009 (1.0003, 1.0015) and 0.9988 (0.9974, 1.0003), respectively. Subgroup analysis (WML volume < 6,200 mm3) showed that the cerebral WML volume (for 0.1 mm3 increase) was positively related to the BD incidence (OR = 1.11, 95% confidence interval [CI] (1.03, 1.21)). Here we show that the cerebral WML volume is positively and non-linearly correlated to the BD risk. Volumetric analysis of WML provide a better understanding of the association between WML and the BD risk, and thereby the pathophysiological mechanisms of BD. Graphical abstract A non-linear relationship between the volume of cerebral white matter lesions (WML) and bipolar disorder (BD) incidence is shown. The cerebral WML volume is positively and non-linearly correlated to the BD risk. The correlation is stronger when the cerebral WML volume was <6,200 mm3.Graphical AbstractA non-linear relationship between the volume of cerebral white matter lesions and bipolar disorder incidence is shown after adjusting for age; sex; lithium, atypical antipsychotic, antiepileptic, and antidepressant drug use; BMI; migraine; smoking; hypertension; diabetes mellitus; substance and alcohol dependency; and anxiety disorder.
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Affiliation(s)
- Hui Du
- Department of Blood Transfusion, Affiliated Xiaolan Hospital, Southern Medical University, Zhongshan, Guangdong, China
| | - Bing Yang
- Neurological Department and Stroke Center, the First Affiliated Hospital of Jinan University and Clinical Neuroscience Institute, Jinan University, Guangzhou, Guangdong, China
| | - Hui Wang
- Department of Neurology, Affiliated Xiaolan Hospital, Southern Medical University, Zhongshan, Guangdong, China
| | - Yaqing Zeng
- Department of Neurology, Affiliated Xiaolan Hospital, Southern Medical University, Zhongshan, Guangdong, China
| | - Jianpin Xin
- Department of Radiology, Affiliated Xiaolan Hospital, Southern Medical University, Zhongshan, Guangdong, China
| | - Xiaoqiang Li
- Department of Neurology, Affiliated Xiaolan Hospital, Southern Medical University, Zhongshan, Guangdong, China
- *Correspondence: Xiaoqiang Li,
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12
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Havlicek DF, Furhang R, Nikulina E, Smith-Salzberg B, Lawless S, Severin SA, Mallaboeva S, Nayab F, Seifert AC, Crary JF, Bergold PJ. A single closed head injury in male adult mice induces chronic, progressive white matter atrophy and increased phospho-tau expressing oligodendrocytes. Exp Neurol 2023; 359:114241. [PMID: 36240881 DOI: 10.1016/j.expneurol.2022.114241] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 09/26/2022] [Accepted: 10/03/2022] [Indexed: 11/05/2022]
Abstract
Traumatic brain injury (TBI) acutely damages the brain; this injury can evolve into chronic neurodegeneration. While much is known about the chronic effects arising from multiple mild TBIs, far less is known about the long-term effects of a single moderate to severe TBI. We found that a single moderate closed head injury to mice induces diffuse axonal injury within 1-day post-injury (DPI). At 14 DPI, injured animals have atrophy of ipsilesional cortex, thalamus, and corpus callosum, with bilateral atrophy of the dorsal fornix. Atrophy of the ipsilesional corpus callosum is accompanied by decreased fractional anisotropy and increased mean and radial diffusivity that remains unchanged between 14 and 180 DPI. Injured animals show an increased density of phospho-tau immunoreactive (pTau+) cells in the ipsilesional cortex and thalamus, and bilaterally in corpus callosum. Between 14 and 180 DPI, atrophy occurs in the ipsilesional ventral fornix, contralesional corpus callosum, and bilateral internal capsule. Diffusion tensor MRI parameters remain unchanged in white matter regions with delayed atrophy. Between 14 and 180 DPI, pTau+ cell density increases bilaterally in corpus callosum, but decreases in cortex and thalamus. The location of pTau+ cells within the ipsilesional corpus callosum changes between 14 and 180 DPI; density of all cells increases including pTau+ or pTau- cells. >90% of the pTau+ cells are in the oligodendrocyte lineage in both gray and white matter. Density of thioflavin-S+ cells in thalamus increases by 180 DPI. These data suggest a single closed head impact produces multiple forms of chronic neurodegeneration. Gray and white matter regions proximal to the impact site undergo early atrophy. More distal white matter regions undergo chronic, progressive white matter atrophy with an increasing density of oligodendrocytes containing pTau. These data suggest a complex chronic neurodegenerative process arising from a single moderate closed head injury.
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Affiliation(s)
- David F Havlicek
- School of Graduate Studies, State University of New York Downstate Health Sciences University, Brooklyn, NY, United States of America
| | - Rachel Furhang
- School of Graduate Studies, State University of New York Downstate Health Sciences University, Brooklyn, NY, United States of America
| | - Elena Nikulina
- Department of Physiology and Pharmacology, State University of New York Downstate Health Sciences University, Brooklyn, NY, United States of America
| | - Bayle Smith-Salzberg
- Department of Physiology and Pharmacology, State University of New York Downstate Health Sciences University, Brooklyn, NY, United States of America
| | - Siobhán Lawless
- School of Graduate Studies, State University of New York Downstate Health Sciences University, Brooklyn, NY, United States of America
| | - Sasha A Severin
- Department of Physiology and Pharmacology, State University of New York Downstate Health Sciences University, Brooklyn, NY, United States of America
| | - Sevara Mallaboeva
- Department of Physiology and Pharmacology, State University of New York Downstate Health Sciences University, Brooklyn, NY, United States of America
| | - Fizza Nayab
- Department of Physiology and Pharmacology, State University of New York Downstate Health Sciences University, Brooklyn, NY, United States of America
| | - Alan C Seifert
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - John F Crary
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Peter J Bergold
- Department of Physiology and Pharmacology, State University of New York Downstate Health Sciences University, Brooklyn, NY, United States of America.
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13
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Deep Grey Matter Volume is Reduced in Amateur Boxers as Compared to Healthy Age-matched Controls. Clin Neuroradiol 2022; 33:475-482. [DOI: 10.1007/s00062-022-01233-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 10/14/2022] [Indexed: 12/23/2022]
Abstract
Abstract
Purpose
Mild traumatic brain injuries (mTBI) sustained during contact sports like amateur boxing are found to have long-term sequelae, being linked to an increased risk of developing neurological conditions like Parkinson’s disease. The aim of this study was to assess differences in volume of anatomical brain structures between amateur boxers and control subjects with a special interest in the affection of deep grey matter structures.
Methods
A total of 19 amateur boxers and 19 healthy controls (HC), matched for age and intelligence quotient (IQ), underwent 3T magnetic resonance imaging (MRI) as well as neuropsychological testing. Body mass index (BMI) was evaluated for every subject and data about years of boxing training and number of fights were collected for each boxer. The acquired 3D high resolution T1 weighted MR images were analyzed to measure the volumes of cortical grey matter (GM), white matter (WM), cerebrospinal fluid (CSF) and deep grey matter structures. Multivariate analysis was applied to reveal differences between groups referencing deep grey matter structures to normalized brain volume (NBV) to adjust for differences in head size and brain volume as well as adding BMI as cofactor.
Results
Total intracranial volume (TIV), comprising GM, WM and CSF, was lower in boxers compared to controls (by 7.1%, P = 0.009). Accordingly, GM (by 5.5%, P = 0.038) and WM (by 8.4%, P = 0.009) were reduced in boxers. Deep grey matter showed statistically lower volumes of the thalamus (by 8.1%, P = 0.006), caudate nucleus (by 11.1%, P = 0.004), putamen (by 8.1%, P = 0.011), globus pallidus (by 9.6%, P = 0.017) and nucleus accumbens (by 13.9%, P = 0.007) but not the amygdala (by 5.5%, P = 0.221), in boxers compared to HC.
Conclusion
Several deep grey matter structures were reduced in volume in the amateur boxer group. Furthermore, longitudinal studies are needed to determine the damage pattern affecting deep grey matter structures and its neuropsychological relevance.
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14
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Kulbe JR, Jain S, Nelson LD, Korley FK, Mukherjee P, Sun X, Okonkwo DO, Giacino JT, Vassar MJ, Robertson CS, McCrea MA, Wang KKW, Temkin N, Mac Donald CL, Taylor SR, Ferguson AR, Markowitz AJ, Diaz-Arrastia R, Manley GT, Stein MB. Association of day-of-injury plasma glial fibrillary acidic protein concentration and six-month posttraumatic stress disorder in patients with mild traumatic brain injury. Neuropsychopharmacology 2022; 47:2300-2308. [PMID: 35717463 PMCID: PMC9630517 DOI: 10.1038/s41386-022-01359-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 05/16/2022] [Accepted: 05/31/2022] [Indexed: 11/10/2022]
Abstract
Several proteins have proven useful as blood-based biomarkers to assist in evaluation and management of traumatic brain injury (TBI). The objective of this study was to determine whether two day-of-injury blood-based biomarkers are predictive of posttraumatic stress disorder (PTSD). We used data from 1143 individuals with mild TBI (mTBI; defined as admission Glasgow Coma Scale [GCS] score 13-15) enrolled in TRACK-TBI, a prospective longitudinal study of level 1 trauma center patients. Plasma glial fibrillary acidic protein (GFAP) and serum high sensitivity C-reactive protein (hsCRP) were measured from blood collected within 24 h of injury. Two hundred and twenty-seven (19.9% of) patients had probable PTSD (PCL-5 score ≥ 33) at 6 months post-injury. GFAP levels were positively associated (Spearman's rho = 0.35, p < 0.001) with duration of posttraumatic amnesia (PTA). There was an inverse association between PTSD and (log)GFAP (adjusted OR = 0.85, 95% CI 0.77-0.95 per log unit increase) levels, but no significant association with (log)hsCRP (adjusted OR = 1.11, 95% CI 0.98-1.25 per log unit increase) levels. Elevated day-of-injury plasma GFAP, a biomarker of glial reactivity, is associated with reduced risk of PTSD after mTBI. This finding merits replication and additional studies to determine a possible neurocognitive basis for this relationship.
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Affiliation(s)
- Jacqueline R. Kulbe
- grid.266100.30000 0001 2107 4242Department of Psychiatry, University of California, San Diego, La Jolla, CA USA
| | - Sonia Jain
- grid.266100.30000 0001 2107 4242Biostatistics Research Center, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA USA
| | - Lindsay D. Nelson
- grid.30760.320000 0001 2111 8460Departments of Neurosurgery and Neurology, Medical College of Wisconsin, Milwaukee, WI USA
| | - Frederick K. Korley
- grid.214458.e0000000086837370Department of Emergency Medicine, University of Michigan, Ann Arbor, MI USA
| | - Pratik Mukherjee
- grid.266102.10000 0001 2297 6811Department of Radiology & Biomedical Imaging, UCSF, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Bioengineering & Therapeutic Sciences, UCSF, San Francisco, CA USA
| | - Xiaoying Sun
- grid.266100.30000 0001 2107 4242Biostatistics Research Center, Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA USA
| | - David O. Okonkwo
- grid.412689.00000 0001 0650 7433Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA USA
| | - Joseph T. Giacino
- grid.38142.3c000000041936754XDepartment of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA USA ,grid.416228.b0000 0004 0451 8771Spaulding Rehabilitation Hospital, Charlestown, MA USA
| | - Mary J. Vassar
- grid.416732.50000 0001 2348 2960Brain and Spinal Cord Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Neurological Surgery, UCSF, San Francisco, CA USA
| | - Claudia S. Robertson
- grid.39382.330000 0001 2160 926XDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX USA
| | - Michael A. McCrea
- grid.30760.320000 0001 2111 8460Departments of Neurosurgery and Neurology, Medical College of Wisconsin, Milwaukee, WI USA
| | - Kevin K. W. Wang
- grid.15276.370000 0004 1936 8091Department of Emergency Medicine, University of Florida, Gainesville, FL USA
| | - Nancy Temkin
- grid.34477.330000000122986657Department of Neurological Surgery, University of Washington, Seattle, WA USA
| | - Christine L. Mac Donald
- grid.34477.330000000122986657Department of Neurological Surgery, University of Washington, Seattle, WA USA
| | - Sabrina R. Taylor
- grid.416732.50000 0001 2348 2960Brain and Spinal Cord Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Neurological Surgery, UCSF, San Francisco, CA USA
| | - Adam R. Ferguson
- grid.416732.50000 0001 2348 2960Brain and Spinal Cord Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA USA
| | - Amy J. Markowitz
- grid.416732.50000 0001 2348 2960Brain and Spinal Cord Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA USA
| | - Ramon Diaz-Arrastia
- grid.25879.310000 0004 1936 8972Department of Neurology, University of Pennsylvania, Philadelphia, PA USA
| | - Geoffrey T. Manley
- grid.416732.50000 0001 2348 2960Brain and Spinal Cord Injury Center, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Department of Neurological Surgery, UCSF, San Francisco, CA USA
| | - Murray B. Stein
- grid.266100.30000 0001 2107 4242Department of Psychiatry, University of California, San Diego, La Jolla, CA USA ,grid.266100.30000 0001 2107 4242School of Public Health, University of California, San Diego, La Jolla, CA USA ,grid.410371.00000 0004 0419 2708VA San Diego Healthcare System, San Diego, CA USA
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15
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San Martín Molina I, Fratini M, Campi G, Burghammer M, Grünewald TA, Salo RA, Narvaez O, Aggarwal M, Tohka J, Sierra A. A multiscale tissue assessment in a rat model of mild traumatic brain injury. J Neuropathol Exp Neurol 2022; 82:71-83. [PMID: 36331507 PMCID: PMC9764078 DOI: 10.1093/jnen/nlac100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Diffusion tensor imaging (DTI) has demonstrated the potential to assess the pathophysiology of mild traumatic brain injury (mTBI) but correlations of DTI findings and pathological changes in mTBI are unclear. We evaluated the potential of ex vivo DTI to detect tissue damage in a mild mTBI rat model by exploiting multiscale imaging methods, histology and scanning micro-X-ray diffraction (SμXRD) 35 days after sham-operation (n = 2) or mTBI (n = 3). There were changes in DTI parameters rostral to the injury site. When examined by histology and SμXRD, there was evidence of axonal damage, reduced myelin density, gliosis, and ultrastructural alterations in myelin that were ongoing at the experimental time point of 35 days postinjury. We assessed the relationship between the 3 imaging modalities by multiple linear regression analysis. In this analysis, DTI and histological parameters were moderately related, whereas SμXRD parameters correlated weakly with DTI and histology. These findings suggest that while DTI appears to distinguish tissue changes at the microstructural level related to the loss of myelinated axons and gliosis, its ability to visualize alterations in myelin ultrastructure is limited. The use of several imaging techniques represents a novel approach to reveal tissue damage and provides new insights into mTBI detection.
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Affiliation(s)
| | - Michela Fratini
- Institute of Nanotechnology-CNR c/o Physics Department, Sapienza University of Rome, Rome, Italy,IRCCS Fondazione Santa Lucia, Rome, Italy
| | | | | | - Tilman A Grünewald
- European Synchrotron Radiation Facility, Grenoble Cedex, France,Aix-Marseille Université, CNRS, Centrale Marseille, Institut Fresnel, Marseille, France
| | - Raimo A Salo
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Omar Narvaez
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Manisha Aggarwal
- Russell H. Morgan Department of Radiology and Radiological Science, John Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jussi Tohka
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Alejandra Sierra
- Send correspondence to: Alejandra Sierra, PhD, A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland (Kuopio Campus), PO Box 1627, Neulaniementie 2, FI-70211 Kuopio, Finland; E-mail:
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16
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Ross DE, Seabaugh J, Seabaugh JM, Barcelona J, Seabaugh D, Wright K, Norwind L, King Z, Graham TJ, Baker J, Lewis T. Updated Review of the Evidence Supporting the Medical and Legal Use of NeuroQuant ® and NeuroGage ® in Patients With Traumatic Brain Injury. Front Hum Neurosci 2022; 16:715807. [PMID: 35463926 PMCID: PMC9027332 DOI: 10.3389/fnhum.2022.715807] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 03/03/2022] [Indexed: 02/05/2023] Open
Abstract
Over 40 years of research have shown that traumatic brain injury affects brain volume. However, technical and practical limitations made it difficult to detect brain volume abnormalities in patients suffering from chronic effects of mild or moderate traumatic brain injury. This situation improved in 2006 with the FDA clearance of NeuroQuant®, a commercially available, computer-automated software program for measuring MRI brain volume in human subjects. More recent strides were made with the introduction of NeuroGage®, commercially available software that is based on NeuroQuant® and extends its utility in several ways. Studies using these and similar methods have found that most patients with chronic mild or moderate traumatic brain injury have brain volume abnormalities, and several of these studies found-surprisingly-more abnormal enlargement than atrophy. More generally, 102 peer-reviewed studies have supported the reliability and validity of NeuroQuant® and NeuroGage®. Furthermore, this updated version of a previous review addresses whether NeuroQuant® and NeuroGage® meet the Daubert standard for admissibility in court. It concludes that NeuroQuant® and NeuroGage® meet the Daubert standard based on their reliability, validity, and objectivity. Due to the improvements in technology over the years, these brain volumetric techniques are practical and readily available for clinical or forensic use, and thus they are important tools for detecting signs of brain injury.
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Affiliation(s)
- David E. Ross
- Virginia Institute of Neuropsychiatry, Midlothian, VA, United States
- NeuroGage LLC, Midlothian, VA, United States
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States
| | - John Seabaugh
- Virginia Institute of Neuropsychiatry, Midlothian, VA, United States
- NeuroGage LLC, Midlothian, VA, United States
- Department of Radiology, St. Mary’s Hospital School of Medical Imaging, Richmond, VA, United States
| | - Jan M. Seabaugh
- Virginia Institute of Neuropsychiatry, Midlothian, VA, United States
- NeuroGage LLC, Midlothian, VA, United States
| | - Justis Barcelona
- Virginia Institute of Neuropsychiatry, Midlothian, VA, United States
- NeuroGage LLC, Midlothian, VA, United States
| | - Daniel Seabaugh
- Virginia Institute of Neuropsychiatry, Midlothian, VA, United States
- NeuroGage LLC, Midlothian, VA, United States
| | - Katherine Wright
- Virginia Institute of Neuropsychiatry, Midlothian, VA, United States
- NeuroGage LLC, Midlothian, VA, United States
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, United States
| | - Lee Norwind
- Karp, Wigodsky, Norwind, Kudel & Gold, P.A., Rockville, MD, United States
| | - Zachary King
- Karp, Wigodsky, Norwind, Kudel & Gold, P.A., Rockville, MD, United States
| | | | - Joseph Baker
- Virginia Institute of Neuropsychiatry, Midlothian, VA, United States
- NeuroGage LLC, Midlothian, VA, United States
- Department of Neuroscience, Christopher Newport University, Newport News, VA, United States
| | - Tanner Lewis
- Virginia Institute of Neuropsychiatry, Midlothian, VA, United States
- NeuroGage LLC, Midlothian, VA, United States
- Department of Undergraduate Studies, University of Virginia, Charlottesville, VA, United States
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17
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Machine Learning Classification of Mild Traumatic Brain Injury Using Whole-Brain Functional Activity: A Radiomics Analysis. DISEASE MARKERS 2021; 2021:3015238. [PMID: 34840627 PMCID: PMC8616658 DOI: 10.1155/2021/3015238] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 11/02/2021] [Indexed: 11/18/2022]
Abstract
Objectives To investigate the classification performance of support vector machine in mild traumatic brain injury (mTBI) from normal controls. Methods Twenty-four mTBI patients (15 males and 9 females; mean age, 38.88 ± 13.33 years) and 24 age and sex-matched normal controls (13 males and 11 females; mean age, 40.46 ± 11.4 years) underwent resting-state functional MRI examination. Seven imaging parameters, including amplitude of low-frequency fluctuation (ALFF), fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), degree centrality (DC), voxel-mirrored homotopic connectivity (VMHC), long-range functional connectivity density (FCD), and short-range FCD, were entered into the classification model to distinguish the mTBI from normal controls. Results The ability for any single imaging parameters to distinguish the two groups is lower than multiparameter combinations. The combination of ALFF, fALFF, DC, VMHC, and short-range FCD showed the best classification performance for distinguishing the two groups with optimal AUC value of 0.778, accuracy rate of 81.11%, sensitivity of 88%, and specificity of 75%. The brain regions with the highest contributions to this classification mainly include bilateral cerebellum, left orbitofrontal cortex, left cuneus, left temporal pole, right inferior occipital cortex, bilateral parietal lobe, and left supplementary motor area. Conclusions Multiparameter combinations could improve the classification performance of mTBI from normal controls by using the brain regions associated with emotion and cognition.
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