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O'Brien MC, Disner SG, Davenport ND, Sponheim SR. The relationship between blast-related mild traumatic brain injury and executive function is moderated by white matter integrity. Brain Imaging Behav 2024:10.1007/s11682-024-00864-z. [PMID: 38448704 DOI: 10.1007/s11682-024-00864-z] [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] [Accepted: 02/06/2024] [Indexed: 03/08/2024]
Abstract
Blast-related mild traumatic brain injury (BR mTBI) is a critical research area in recent combat veterans due to increased prevalence of survived blasts. Post-BR mTBI outcomes are highly heterogeneous and defining neurological differences may help in discrimination and prediction of cognitive outcomes. This study investigates whether white matter integrity, measured with diffusion tensor imaging (DTI), could influence how remote BR mTBI history is associated with executive control. The sample included 151 Veterans from the Minneapolis Veterans Affairs Medical Center who were administered a clinical/TBI assessment, neuropsychological battery, and DTI scan as part of a larger battery. From previous research, six white matter tracts were identified as having a putative relationship with blast severity: the cingulum, hippocampal cingulum, corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus and uncinate. Fractional anisotropy (FA) of the a priori selected white matter tracts and report of BR mTBI were used as predictors of Trail-Making Test B (TMT-B) performance in a multiple linear regression model. Statistical analysis revealed that FA of the hippocampal cingulum moderated the association between report of at least one BR mTBI and poorer TMT-B performance (p < 0.008), such that lower FA value was associated with worse TMT-B outcomes in individuals with BR mTBI. No significant moderation existed for other selected tracts, and the effect was not observed with predictors aside from history of BR mTBI. Investigation at the individual-tract level may lead to a deeper understanding of neurological differences between blast-related and non-blast related injuries.
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Affiliation(s)
- Molly C O'Brien
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA.
- University of Minnesota, Twin Cities, Minneapolis, MN, USA.
| | - Seth G Disner
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA
- University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Nicholas D Davenport
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA
- University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Scott R Sponheim
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA
- University of Minnesota, Twin Cities, Minneapolis, MN, USA
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Müller HP, Roselli F, Rasche V, Kassubek J. Diffusion Tensor Imaging-Based Studies at the Group-Level Applied to Animal Models of Neurodegenerative Diseases. Front Neurosci 2020; 14:734. [PMID: 32982659 PMCID: PMC7487414 DOI: 10.3389/fnins.2020.00734] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 06/22/2020] [Indexed: 12/11/2022] Open
Abstract
The understanding of human and non-human microstructural brain alterations in the course of neurodegenerative diseases has substantially improved by the non-invasive magnetic resonance imaging (MRI) technique of diffusion tensor imaging (DTI). Animal models (including disease or knockout models) allow for a variety of experimental manipulations, which are not applicable to humans. Thus, the DTI approach provides a promising tool for cross-species cross-sectional and longitudinal investigations of the neurobiological targets and mechanisms of neurodegeneration. This overview with a systematic review focuses on the principles of DTI analysis as used in studies at the group level in living preclinical models of neurodegeneration. The translational aspect from in-vivo animal models toward (clinical) applications in humans is covered as well as the DTI-based research of the non-human brains' microstructure, the methodological aspects in data processing and analysis, and data interpretation at different abstraction levels. The aim of integrating DTI in multiparametric or multimodal imaging protocols will allow the interrogation of DTI data in terms of directional flow of information and may identify the microstructural underpinnings of neurodegeneration-related patterns.
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Affiliation(s)
| | - Francesco Roselli
- Department of Neurology, University of Ulm, Ulm, Germany.,German Center for Neurodegenerative Diseases (DZNE), Ulm, Germany
| | - Volker Rasche
- Core Facility Small Animal MRI, University of Ulm, Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany
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Bigler ED. Structural neuroimaging in sport-related concussion. Int J Psychophysiol 2018; 132:105-123. [DOI: 10.1016/j.ijpsycho.2017.09.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Revised: 09/03/2017] [Accepted: 09/07/2017] [Indexed: 10/18/2022]
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Murphy MA, Mun S, Horstemeyer MF, Baskes MI, Bakhtiary A, LaPlaca MC, Gwaltney SR, Williams LN, Prabhu RK. Molecular dynamics simulations showing 1-palmitoyl-2-oleoyl-phosphatidylcholine (POPC) membrane mechanoporation damage under different strain paths. J Biomol Struct Dyn 2018; 37:1346-1359. [DOI: 10.1080/07391102.2018.1453376] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- M. A. Murphy
- Center for Advanced Vehicular Systems (CAVS), Mississippi State University, Mississippi State, MS, USA
- Department of Agricultural and Biological Engineering, Mississippi State University, Mississippi State, MS, USA
| | - Sungkwang Mun
- Center for Advanced Vehicular Systems (CAVS), Mississippi State University, Mississippi State, MS, USA
| | - M. F. Horstemeyer
- Center for Advanced Vehicular Systems (CAVS), Mississippi State University, Mississippi State, MS, USA
- Department of Mechanical Engineering, Mississippi State University, Mississippi State, MS, USA
| | - M. I. Baskes
- Department of Aerospace Engineering, Mississippi State University, Mississippi State, MS, USA
- Los Alamos National Laboratory, Los Alamos, NM, USA
| | - A. Bakhtiary
- Center for Advanced Vehicular Systems (CAVS), Mississippi State University, Mississippi State, MS, USA
- Department of Agricultural and Biological Engineering, Mississippi State University, Mississippi State, MS, USA
| | - Michelle C. LaPlaca
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Steven R. Gwaltney
- Department of Chemistry, Mississippi State University, Mississippi State, MS 39762, USA
- Center for Computational Sciences, Mississippi State University, Mississippi State, MS 39762, USA
| | - Lakiesha N. Williams
- Center for Advanced Vehicular Systems (CAVS), Mississippi State University, Mississippi State, MS, USA
- Department of Agricultural and Biological Engineering, Mississippi State University, Mississippi State, MS, USA
| | - R. K. Prabhu
- Center for Advanced Vehicular Systems (CAVS), Mississippi State University, Mississippi State, MS, USA
- Department of Agricultural and Biological Engineering, Mississippi State University, Mississippi State, MS, USA
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Garimella HT, Kraft RH. Modeling the mechanics of axonal fiber tracts using the embedded finite element method. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2017; 33. [PMID: 27502006 DOI: 10.1002/cnm.2823] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2015] [Revised: 07/11/2016] [Accepted: 07/16/2016] [Indexed: 05/10/2023]
Abstract
A subject-specific human head finite element model with embedded axonal fiber tractography obtained from diffusion tensor imaging was developed. The axonal fiber tractography finite element model was coupled with the volumetric elements in the head model using the embedded element method. This technique enables the calculation of axonal strains and real-time tracking of the mechanical response of the axonal fiber tracts. The coupled model was then verified using pressure and relative displacement-based (between skull and brain) experimental studies and was employed to analyze a head impact, demonstrating the applicability of this method in studying axonal injury. Following this, a comparison study of different injury criteria was performed. This model was used to determine the influence of impact direction on the extent of the axonal injury. The results suggested that the lateral impact loading is more dangerous compared to loading in the sagittal plane, a finding in agreement with previous studies. Through this analysis, we demonstrated the viability of the embedded element method as an alternative numerical approach for studying axonal injury in patient-specific human head models.
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Affiliation(s)
- Harsha T Garimella
- Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Reuben H Kraft
- Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
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Narayana PA. White matter changes in patients with mild traumatic brain injury: MRI perspective. Concussion 2017; 2:CNC35. [PMID: 30202576 PMCID: PMC6093760 DOI: 10.2217/cnc-2016-0028] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2016] [Accepted: 02/10/2017] [Indexed: 12/20/2022] Open
Abstract
This review focuses on white matter (WM) changes in mild traumatic brain injury (mTBI) as assessed by multimodal MRI. All the peer reviewed publications on WM changes in mTBI from January 2011 through September 2016 are included in this review. This review is organized as follows: introduction to mTBI, the basics of multimodal MRI techniques that are potentially useful for probing the WM integrity, summary and critical evaluation of the published literature on the application of multimodal MRI techniques to assess the changes of WM in mTBI, and correlation of MRI measures with behavioral deficits. The MRI–pathology correlation studies based on preclinical models of mTBI are also reviewed. Finally, the author's perspective of future research directions is described.
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Affiliation(s)
- Ponnada A Narayana
- Department of Diagnostic & Interventional Imaging, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
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Abstract
OBJECTIVES Recent advances in neuroimaging methodologies sensitive to axonal injury have made it possible to assess in vivo the extent of traumatic brain injury (TBI) -related disruption in neural structures and their connections. The objective of this paper is to review studies examining connectivity in TBI with an emphasis on structural and functional MRI methods that have proven to be valuable in uncovering neural abnormalities associated with this condition. METHODS We review studies that have examined white matter integrity in TBI of varying etiology and levels of severity, and consider how findings at different times post-injury may inform underlying mechanisms of post-injury progression and recovery. Moreover, in light of recent advances in neuroimaging methods to study the functional connectivity among brain regions that form integrated networks, we review TBI studies that use resting-state functional connectivity MRI methodology to examine neural networks disrupted by putative axonal injury. RESULTS The findings suggest that TBI is associated with altered structural and functional connectivity, characterized by decreased integrity of white matter pathways and imbalance and inefficiency of functional networks. These structural and functional alterations are often associated with neurocognitive dysfunction and poor functional outcomes. CONCLUSIONS TBI has a negative impact on distributed brain networks that lead to behavioral disturbance.
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