Cited by 81Traumatic Brain Injury ResearchAutomotive and Human Injury BiomechanicsPosttraumatic Stress Disorder Research

Functional and Structural Neuroimaging Correlates of Repetitive Low-Level Blast Exposure in Career Breachers

Open access
Stone, James R., Avants, Brian B., Tustison, Nicholas J., Wassermann, Eric M., Gill, Jessica, Polejaeva, Elena, Dell, Kristine C., Carr, Walter +11 more·2020·Journal of Neurotrauma

Abstract

Combat military and civilian law enforcement personnel may be exposed to repetitive low-intensity blast events during training and operations. Persons who use explosives to gain entry (i.e., breach) into buildings are known as “breachers” or dynamic entry personnel. Breachers operate under the guidance of established safety protocols, but despite these precautions, breachers who are exposed to low-level blast throughout their careers frequently report performance deficits and symptoms to healthcare providers. Although little is known about the etiology linking blast exposure to clinical symptoms in humans, animal studies demonstrate network-level changes in brain function, alterations in brain morphology, vascular and inflammatory changes, hearing loss, and even alterations in gene expression after repeated blast exposure. To explore whether similar effects occur in humans, we collected a comprehensive data battery from 20 experienced breachers exposed to blast throughout their careers and 14 military and law enforcement controls. This battery included neuropsychological assessments, blood biomarkers, and magnetic resonance imaging measures, including cortical thickness, diffusion tensor imaging of white matter, functional connectivity, and perfusion. To better understand the relationship between repetitive low-level blast exposure and behavioral and imaging differences in humans, we analyzed the data using similarity-driven multi-view linear reconstruction (SiMLR). SiMLR is specifically designed for multiple modality statistical integration using dimensionality-reduction techniques for studies with high-dimensional, yet sparse, data (i.e., low number of subjects and many data per subject). We identify significant group effects in these data spanning brain structure, function, and blood biomarkers.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1089/neu.2020.7141

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • If there is cumulative brain damage from repetitive, sub-concussive, low-level blast exposures, it was not apparent on the study's cognitive testing.

    “If there is cumulative brain damage from repetitive, sub-concussive, low-level blast exposures as evidence from other evaluation techniques suggests (Belding et al., 2021; Goldstein et al., 2012; Stone et al., 2020; Tate et al., 2013), it was not apparent on our cognitive testing.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 72

  1. [1]Warden D. (2006). Military TBI during the Iraq and Afghanistan wars. J. Head Trauma Rehabil. 21, 398– 402 16983225
  2. [2]Elder G.A., and Cristian A. (2009). Blast-related mild traumatic brain injury: Mechanisms of injury and impact on clinical care. Mt. Sinai J. Med. 76, 111– 118 19306373
  3. [3]Carr W., Stone J.R., Walilko T., Young L.A., Snook T.L., Paggi M.E., Tsao J.W., Jankosky C.J., Parish R.V., and Ahlers S.T. (2016). Repeated low-level blast exposure: a descriptive human subjects study. Mil. Med. 181, 28– 39 27168550
  4. [4]Gill J., Cashion A., Osier N., Arcurio L., Motamedi V., Dell K.C., Carr W., Kim H.-S., Yun S., Walker P., Ahlers S., LoPresti M., and Yarnell A. (2017). Moderate blast exposure alters gene expression and levels of amyloid precursor protein. Neurol Genet. 3, e186 28975156 PMC5618107
  5. [5]Gill J., Motamedi V., Osier N., Dell K., Arcurio L., Carr W., Walker P., Ahlers S., LoPresti M., and Yarnell A. (2017). Moderate blast exposure results in increased IL-6 and TNFα in peripheral blood. Brain Behav. Immun. 65, 90– 94 28232173 PMC5537025
  6. [7]Hirsch F.G. (1966). Effects of overpressure on the ear—a review. DASA Report 1858. Technical Progress Report on Contract No. DA-49-146-XZ-372. Lovelace Foundation for Medical Education and Research: Albuquerque, New Mexico
  7. [8]Bowen I.G., Fletcher E.R., Richmond D.R., Hirsch F.G., and White C.S. (1968). Biophysical mechanisms and scaling procedures applicable in assessing responses of the thorax energized by air-blast overpressures or by nonpenetrating missiles. Ann. N. Y. Acad. Sci. 152, 122– 146 5257525
  8. [9]Michael A.P., Stout J., Roskos P.T., Bolzenius J., Gfeller J., Mogul D., and Bucholz R. (2015). Evaluation of cortical thickness after traumatic brain injury in military veterans. J. Neurotrauma 32, 1751– 1758 26131617
  9. [10]Sharp D.J., Scott G., and Leech R. (2014). Network dysfunction after traumatic brain injury. Nat. Rev. Neurol. 10, 156– 66 24514870
  10. [11]Elder G.A., Gama Sosa M.A., De Gasperi R., Stone J.R., Dickstein D.L., Haghighi F., Hof P.R., and Ahlers S.T. (2015). Vascular and inflammatory factors in the pathophysiology of blast-induced brain injury. Front. Neurol. 6, 48 25852632 PMC4360816
  11. [12]Ashburner J., and Friston K.J. (2000). Voxel-based morphometry—the methods. Neuroimage 11, 805– 821 10860804
  12. [13]Worsley K.J., Evans A.C., Marrett S., and Neelin P. (1992). A three-dimensional statistical analysis for cbf activation studies in human brain. J. Cereb. Blood Flow Metab. 12, 900– 918 1400644
  13. [15]Avants B.B., Hutchison R.M., Mikulskis A., Salinas-Valenzuela C., Hargreaves R., Beaver J., and Chiao, P.; Alzheimer's Disease Neuroimaging Initiative. (2019). Amyloid beta-positive subjects exhibit longitudinal network-specific reductions in spontaneous brain activity. Neurobiol. Aging 74, 191– 201 30471630
  14. [16]Avants B., Dhillon P., Kandel B.M., Cook P.A., McMillan C.T., Grossman M., and Gee J.C. (2012). Eigenanatomy improves detection power for longitudinal cortical change. Med. Image Comput. Comput. Assist. Interv. 15, 206– 213 PMC3653970 23286132
  15. [17]Dhillon P.S., Wolk D.A., Das S.R., Ungar L.H., Gee J.C., and Avants B.B. (2014). Subject-specific functional parcellation via prior based eigenanatomy. Neuroimage 99, 14– 27 24852460 PMC4382016
  16. [18]Avants B.B., Libon D.J., Rascovsky K., Boller A., McMillan C.T., Massimo L., Coslett H.B., Chatterjee A., Gross R.G., and Grossman M. (2014). Sparse canonical correlation analysis relates network-level atrophy to multivariate cognitive measures in a neurodegenerative population. Neuroimage 84, 698– 711 24096125 PMC3911786
  17. [19]Kandel B.M., Wang D.J.J., Gee J.C., and Avants B.B. (2015). Eigenanatomy: Sparse dimensionality reduction for multi-modal medical image analysis. Methods 73, 43– 53 25448483 PMC4329066
  18. [20]Olivera A., Lejbman N., Jeromin A., French L.M., Kim H.-S., Cashion A., Mysliwiec V., Diaz-Arrastia R., and Gill J. (2015). Peripheral total tau in military personnel who sustain traumatic brain injuries during deployment. JAMA Neurol. 72, 1109– 16 26237304
  19. [21]Avants B.B., Duda J.T., Kilroy E., Krasileva K., Jann K., Kandel B.T., Tustison N.J., Yan L., Jog M., Smith R., Wang Y., Dapretto M., and Wang D.J.J. (2015). The pediatric template of brain perfusion. Sci. Data 2, 150003 25977810 PMC4413243
  20. [22]Avants B.B., Yushkevich P., Pluta J., Minkoff D., Korczykowski M., Detre J., and Gee J.C. (2010). The optimal template effect in hippocampus studies of diseased populations. Neuroimage 49, 2457– 2466 19818860 PMC2818274
  21. [23]Tustison N.J., Cook P.A., Klein A., Song G., Das S.R., Duda J.T., Kandel B.M., Strien N. van, Stone J.R., Gee J.C., and Avants B.B. (2014). Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements. Neuroimage 99, 166– 179 24879923
  22. [25]Tustison N.J., Avants B.B., Cook P.A., Zheng Y., Egan A., Yushkevich P.A., and Gee J.C. (2010). N4ITK: improved N3 bias correction. IEEE Trans. Med. Imaging 29, 1310– 1320 20378467 PMC3071855
  23. [26]Avants B.B., Tustison N.J., Wu J., Cook P.A., and Gee J.C. (2011). An open source multivariate framework for n-tissue segmentation with evaluation on public data. Neuroinformatics 9, 381– 400 21373993 PMC3297199
  24. [27]Das S.R., Avants B.B., Grossman M., and Gee J.C. (2009). Registration based cortical thickness measurement. Neuroimage 45, 867– 879 19150502 PMC2836782
  25. [28]Veraart J., Novikov D.S., Christiaens D., Ades-Aron B., Sijbers J., and Fieremans E. (2016). Denoising of diffusion MRI using random matrix theory. Neuroimage 142, 394– 406 27523449 PMC5159209
  26. [29]Dhollander T., Raffelt D., and Connelly A. (2016). Unsupervised 3-tissue response function estimation from single-shell or multi-shell diffusion MR data without a co-registered T1 image. Presented at the ISMRM Workshop on Breaking the Barriers of Diffusion MRI
  27. [30]Veraart J., Sijbers J., Sunaert S., Leemans A., and Jeurissen B. (2013). Weighted linear least squares estimation of diffusion MRI parameters: strengths, limitations, and pitfalls. Neuroimage 81, 335– 346 23684865
  28. [31]Avants B.B., Tustison N.J., Song G., Cook P.A., Klein A., and Gee J.C. (2011). A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage 54, 2033– 2044 20851191 PMC3065962
  29. [32]Power J.D., Barnes K.A., Snyder A.Z., Schlaggar B.L., and Petersen S.E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59, 2142– 2154 22019881 PMC3254728
  30. [33]Behzadi Y., Restom K., Liau J., and Liu T.T. (2007). A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage 37, 90– 101 17560126 PMC2214855
  31. [34]Wink A.M., and Roerdink J.B.T.M. (2004). Denoising functional MR images: a comparison of wavelet denoising and Gaussian smoothing. IEEE Trans. Med. Imaging 23, 374– 387 15027530
  32. [35]Zou Q.-H., Zhu C.-Z., Yang Y., Zuo X.-N., Long X.-Y., Cao Q.-J., Wang Y.-F., and Zang Y.-F. (2008). An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF. J. Neurosci. Methods 172, 137– 141 18501969 PMC3902859
  33. [37]Ostergaard L., Sorensen A.G., Kwong K.K., Weisskoff R.M., Gyldensted C., and Rosen B.R. (1996). High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part II: experimental comparison and preliminary results. Magn. Reson. Med. 36, 726– 736 8916023
  34. [38]Mlynash M., Eyngorn I., Bammer R., Moseley M., and Tong D.C. (2005). Automated method for generating the arterial input function on perfusion-weighted MR imaging: validation in patients with stroke. AJNR Am. J. Neuroradiol. 26, 1479– 1486 15956519 PMC8149072
  35. [39]Avants B.B., Yushkevich P., Pluta J., Minkoff D., Korczykowski M., Detre J., and Gee J.C. (2010). The optimal template effect in hippocampus studies of diseased populations. Neuroimage 49, 2457– 2466 19818860 PMC2818274
  36. [40]Avants B.B., Tustison N.J., Stauffer M., Song G., Wu B., and Gee J.C. (2014). The Insight ToolKit image registration framework. Front. Neuroinform. 8, 44 24817849 PMC4009425
  37. [41]Avants B.B., Tustison N.J., and Stone J.R. (2020). SiMLR for learning sparse multi-view brain embeddings. BioRxiv (under review in Neuroinformatics)
  38. [42]Cook P.A., McMillan C.T., Avants B.B., Peelle J.E., Gee J.C., and Grossman M. (2014). Relating brain anatomy and cognitive ability using a multivariate multimodal framework. Neuroimage 99, 477– 486 24830834 PMC4151353
  39. [43]McMillan C.T., Irwin D.J., Avants B.B., Powers J., Cook P.A., Toledo J.B., McCarty Wood E., Van Deerlin V.M., Lee V.M.-Y., Trojanowski J.Q., and Grossman M. (2013). White matter imaging helps dissociate tau from TDP-43 in frontotemporal lobar degeneration. J. Neurol. Neurosurg. Psychiatry 84, 949– 955 23475817 PMC3737288
  40. [45]Mac Donald C.L., Johnson A.M., Cooper D., Nelson E.C., Werner N.J., Shimony J.S., Snyder A.Z., Raichle M.E., Witherow J.R., Fang R., Flaherty S.F., and Brody D.L. (2011). Detection of blast-related traumatic brain injury in U.S. Military personnel. N. Engl. J. Med. 364, 2091– 2100 21631321 PMC3146351
  41. [46]Smith S.M., Jenkinson M., Johansen-Berg H., Rueckert D., Nichols T.E., Mackay C.E., Watkins K.E., Ciccarelli O., Cader M.Z., Matthews P.M., and Behrens T.E.J. (2006). Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31, 1487– 1505 16624579
  42. [48]Patel P., Taylor D., and Park M.S. (2019). Characteristics of traumatic brain injury during operation enduring freedom-afghanistan: a retrospective case series. Neurosurg. Focus 47, E13 31675708
  43. [50]Mac Donald C.L., Johnson A.M., Wierzechowski L., Kassner E., Stewart T., Nelson E.C., Werner N.J., Adam O.R., Rivet D.J., Flaherty S.F., Oh J.S., Zonies D., Fang R., and Brody D.L. (2017). Outcome trends after us military concussive traumatic brain injury. J. Neurotrauma 34, 2206– 2219 27198861 PMC5510713
  44. [51]Larres D.T., Carr W., Gonzales E.G., and Hawley J.S. (2016). The natural history of acute recovery of blast-induced mild traumatic brain injury: a case series during war. Mil. Med. 181, 23– 27 27168549
  45. [52]Eierud C., Nathan D.E., Bonavia G.H., Ollinger J., and Riedy G. (2019). Cortical thinning in military blast compared to non-blast persistent mild traumatic brain injuries. Neuroimage Clin. 22, 101793 30939340 PMC6446073
  46. [53]Clark A.L., Merritt V.C., Bigler E.D., Bangen K.J., Werhane M., Sorg S.F., Bondi M.W., Schiehser D.M., and Delano-Wood L. (2018). Blast-exposed veterans with mild traumatic brain injury show greater frontal cortical thinning and poorer executive functioning. Front. Neurol. 9, 873 30473678 PMC6237912
  47. [54]Salat D.H., Robinson M.E., Miller D.R., Clark D.C., and McGlinchey R.E. (2017). Neuroimaging of deployment-associated traumatic brain injury (TBI) with a focus on mild TBI (mTBI) since 2009. Brain Inj. 31, 1204– 1219 28981347 PMC9206728
  48. [55]Tate D.F., York G.E., Reid M.W., Cooper D.B., Jones L., Robin D.A., Kennedy J.E., and Lewis J. (2014). Preliminary findings of cortical thickness abnormalities in blast injured service members and their relationship to clinical findings. Brain Imaging Behav. 8, 102– 109 24100952 PMC4714342
  49. [56]Clausen A.N., Clarke E., Phillips R.D., Haswell C., and Morey R.A. (2020). Combat exposure, posttraumatic stress disorder, and head injuries differentially relate to alterations in cortical thickness in military veterans. Neuropsychopharmacology 45, 491– 498 31600766 PMC6969074
  50. [57]Newsome M.R., Wilde E.A., Bigler E.D., Liu Q., Mayer A.R., Taylor B.A., Steinberg J.L., Tate D.F., Abildskov T.J., Scheibel R.S., Walker W.C., and Levin H.S. (2018). Functional brain connectivity and cortical thickness in relation to chronic pain in post-911 veterans and service members with mTBI. Brain Inj. 32, 1235– 1243 30047797
  51. [58]Shively S.B., Horkayne-Szakaly I., Jones R.V., Kelly J.P., Armstrong R.C., and Perl D.P. (2016). Characterisation of interface astroglial scarring in the human brain after blast exposure: a post-mortem case series. Lancet Neurol. 15, 944– 953 27291520
  52. [59]Clark A.L., Bangen K.J., Sorg S.F., Schiehser D.M., Evangelista N.D., McKenna B., Liu T.T., and Delano-Wood L. (2017). Dynamic association between perfusion and white matter integrity across time since injury in Veterans with history of TBI. Neuroimage Clin. 14, 308– 315 28210542 PMC5299206
  53. [60]Kou Z., Ye Y., and Haacke E.M. (2015). Evaluating the role of reduced oxygen saturation and vascular damage in traumatic brain injury using magnetic resonance perfusion-weighted imaging and susceptibility-weighted imaging and mapping. Top. Magn. Reson. Imaging 24, 253– 265 26502307
  54. [61]Doshi H., Wiseman N., Liu J., Wang W., Welch R.D., O'Neil B.J., Zuk C., Wang X., Mika V., Szaflarski J.P., Haacke E.M., and Kou Z. (2015). Cerebral hemodynamic changes of mild traumatic brain injury at the acute stage. PLoS One 10, e0118061 25659079 PMC4320047
  55. [62]Liu W., Wang B., Wolfowitz R., Yeh P.-H., Nathan D.E., Graner J., Tang H., Pan H., Harper J., Pham D., Oakes T.R., French L.M., and Riedy G. (2013). Perfusion deficits in patients with mild traumatic brain injury characterized by dynamic susceptibility contrast MRI. NMR Biomed. 26, 651– 663 23456696
  56. [63]Heyburn L., Abutarboush R., Goodrich S., Urioste R., Batuure A., Statz J., Wilder D., Ahlers S.T., Long J.B., and Sajja V.S.S.S. (2019). Repeated low-level blast overpressure leads to endovascular disruption and alterations in TDP-43 and Piezo2 in a rat model of blast TBI. Front. Neurol. 10, 766 31417481 PMC6682625
  57. [64]Gama Sosa M.A., De Gasperi R., Perez Garcia G.S., Perez G.M., Searcy C., Vargas D., Spencer A., Janssen P.L., Tschiffely A.E., McCarron R.M., Ache B., Manoharan R., Janssen W.G., Tappan S.J., Hanson R.W., Gandy S., Hof P.R., Ahlers S.T., and Elder G.A. (2019). Low-level blast exposure disrupts gliovascular and neurovascular connections and induces a chronic vascular pathology in rat brain. Acta Neuropathol. Commun. 7, 6 30626447 PMC6327415
  58. [65]Rodriguez U.A., Zeng Y., Deyo D., Parsley M.A., Hawkins B.E., Prough D.S., and DeWitt D.S. (2018). Effects of mild blast traumatic brain injury on cerebral vascular, histopathological, and behavioral outcomes in rats. J. Neurotrauma 35, 375– 392 29160141 PMC5784797
  59. [66]Grossman E.J., Jensen J.H., Babb J.S., Chen Q., Tabesh A., Fieremans E., Xia D., Inglese M., and Grossman R.I. (2013). Cognitive impairment in mild traumatic brain injury: a longitudinal diffusional kurtosis and perfusion imaging study. AJNR Am. J. Neuroradiol. 34, 951–957, S1– S3 23179649 PMC3908903
  60. [67]Wallace E.J., Mathias J.L., and Ward L. (2018). Diffusion tensor imaging changes following mild, moderate and severe adult traumatic brain injury: a meta-analysis. Brain Imaging Behav. 12, 1607– 1621 29383621
  61. [68]Rajesh A., Cooke G.E., Monti J.M., Jahn A., Daugherty A.M., Cohen N.J., and Kramer A.F. (2017). Differences in brain architecture in remote mild traumatic brain injury. J. Neurotrauma 34, 3280– 3287 28726543 PMC6913796
  62. [69]Miller D.R., Hayes J.P., Lafleche G., Salat D.H., and Verfaellie M. (2017). White matter abnormalities are associated with overall cognitive status in blast-related mTBI. Brain Imaging Behav. 11, 1129– 1138 27704406 PMC5378671
  63. [70]Newcombe V.F.J., Correia M.M., Ledig C., Abate M.G., Outtrim J.G., Chatfield D., Geeraerts T., Manktelow A.E., Garyfallidis E., Pickard J.D., Sahakian B.J., Hutchinson P.J.A., Rueckert D., Coles J.P., Williams G.B., and Menon D.K. (2016). Dynamic changes in white matter abnormalities correlate with late improvement and deterioration following TBI: a diffusion tensor imaging study. Neurorehabil. Neural Repair 30, 49– 62 25921349
  64. [71]McDonald S., Rushby J.A., Dalton K.I., Allen S.K., and Parks N. (2018). The role of abnormalities in the corpus callosum in social cognition deficits after traumatic brain injury. Soc. Neurosci. 13, 471– 479 28712330
  65. [72]Dodd A.B., Epstein K., Ling J.M., and Mayer A.R. (2014). Diffusion tensor imaging findings in semi-acute mild traumatic brain injury. J. Neurotrauma 31, 1235– 1248 24779720
  66. [73]Adnan A., Crawley A., Mikulis D., Moscovitch M., Colella B., and Green R. (2013). Moderate-severe traumatic brain injury causes delayed loss of white matter integrity: evidence of fornix deterioration in the chronic stage of injury. Brain Inj. 27, 1415– 1422 24102365
  67. [74]Mac Donald C.L., Barber J., Andre J., Evans N., Panks C., Sun S., Zalewski K., Elizabeth Sanders R., and Temkin N. (2017). 5-year imaging sequelae of concussive blast injury and relation to early clinical outcome. Neuroimage Clin. 14, 371– 378 28243574 PMC5320067
  68. [75]Hayes J.P., Miller D.R., Lafleche G., Salat D.H., and Verfaellie M. (2015). The nature of white matter abnormalities in blast-related mild traumatic brain injury. Neuroimage Clin. 8, 148– 156 26106539 PMC4473287
  69. [76]Sours C., George E.O., Zhuo J., Roys S., and Gullapalli R.P. (2015). Hyper-connectivity of the thalamus during early stages following mild traumatic brain injury. Brain Imaging Behav. 9, 550– 563 26153468 PMC4577461
  70. [77]Palacios E.M., Sala-Llonch R., Junque C., Roig T., Tormos J.M., Bargallo N., and Vendrell P. (2013). Resting-state functional magnetic resonance imaging activity and connectivity and cognitive outcome in traumatic brain injury. JAMA Neurol. 70, 845– 851 23689958
  71. [79]Sullivan D.R., Hayes J.P., Lafleche G., Salat D.H., and Verfaellie M. (2018). Functional brain alterations associated with cognitive control in blast-related mild traumatic brain injury. J. Int. Neuropsychol. Soc. 24, 662– 672 29954465 PMC6108927
  72. [80]Blanchard E.B., Jones Alexander J., Buckley T.C., and Forneris C.A. (1996). Psychometric properties of the PTSD Checklist (PCL). Behav. Res. Ther. 34, 669– 673 8870294

Cited by

Sorted by citations

Authors
Stone, J. R., Avants, B. B., Tustison, N. J., Wassermann, E. M., Gill, J., Polejaeva, E., Dell, K. C., Carr, W., Yarnell, A. M., LoPresti, M. L., Walker, P., O'Brien, M., Domeisen, N., Quick, A., Modica, C. M., Hughes, J. D., Haran, F. J., Goforth, C., & Ahlers, S. T.
Affiliations
  • University of Virginia (US)
  • National Institutes of Health (US)
  • University of Florida (US)
  • Pennsylvania State University (US)
  • Oak Ridge Institute for Science and Education (US)
  • Uniformed Services University of the Health Sciences (US)
  • Walter Reed Army Institute of Research (US)
  • United States Department of Defense (US)
  • University of Glasgow (GB)
  • Naval Medical Research Command (US)
Corresponding author
Stone, James R.
Venue
Journal of Neurotrauma
Published
2020-11-06
Volume
37
Issue
23
Pages
2468-2481
ISSN
  • 0897-7151 (ISSN-L)
  • 1557-9042
OpenAlex
W3087319203
Cited by
81
References
4
Citations by year
2026: 13 · 2025: 10 · 2024: 27 · 2023: 6 · 2022: 12 · 2021: 10 · 2020: 1 · 2015: 1
FWCI
5.19
Type
journal article
Language
en
Open access
Locations
  • Journal of Neurotrauma (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Epidemiology › Traumatic Brain Injury Research
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Automotive and Human Injury Biomechanics
  • Social Sciences › Psychology › Clinical Psychology › Posttraumatic Stress Disorder Research
Keywords
blast-induced neurotrauma, cortical thickness, white matter integrity, functional connectivity, cerebral perfusion, blood biomarkers
MeSH terms
Brain Injuries, Traumatic, Adult, Blast Injuries, Brain, Humans, Male, Middle Aged, Neuroimaging

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review