Hostname: page-component-76fb5796d-wq484 Total loading time: 0 Render date: 2024-04-30T00:51:14.066Z Has data issue: false hasContentIssue false
  • English
  • Français

Longitudinal Changes in Resting State Connectivity and White Matter Integrity in Adolescents With Sports-Related Concussion

Published online by Cambridge University Press:  24 August 2018

Donna L. Murdaugh Open the ORCID record for Donna L. Murdaugh [Opens in a new window] ,
Tricia Z. King ,
Binjian Sun ,
Richard A. Jones ,
Kim E. Ono ,
Andrew Reisner  and
Thomas G. Burns
Donna L. Murdaugh*
Affiliation:
Department of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama
Tricia Z. King
Affiliation:
Department of Psychology and the Neuroscience Institute, Georgia State University, Atlanta, Georgia
Binjian Sun
Affiliation:
Department of Radiology, Children’s Healthcare of Atlanta, Atlanta, Georgia
Richard A. Jones
Affiliation:
Department of Radiology, Children’s Healthcare of Atlanta, Atlanta, Georgia
Kim E. Ono
Affiliation:
Department of Neuropsychology, Children’s Healthcare of Atlanta, Atlanta, Georgia
Andrew Reisner
Affiliation:
Department of Neurosurgery, Children’s Healthcare of Atlanta, Atlanta, Georgia
Thomas G. Burns
Affiliation:
Department of Neuropsychology, Children’s Healthcare of Atlanta, Atlanta, Georgia
*
Correspondence and reprint requests to: Donna L. Murdaugh, 1600 7th Avenue S, Lowder 500, Birmingham, AL 35233. E-mail: dlmurdaugh@gmail.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives: The aim of this study was to investigate alterations in functional connectivity, white matter integrity, and cognitive abilities due to sports-related concussion (SRC) in adolescents using a prospective longitudinal design. Methods: We assessed male high school football players (ages 14–18) with (n=16) and without (n=12) SRC using complementary resting state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI) along with cognitive performance using the Immediate Post-Concussive Assessment and Cognitive Testing (ImPACT). We assessed both changes at the acute phase (<7 days post-SRC) and at 21 days later, as well as, differences between athletes with SRC and age- and team-matched control athletes. Results: The results revealed rs-fMRI hyperconnectivity within posterior brain regions (e.g., precuneus and cerebellum), and hypoconnectivity in more anterior areas (e.g., inferior and middle frontal gyri) when comparing SRC group to control group acutely. Performance on the ImPACT (visual/verbal memory composites) was correlated with resting state network connectivity at both time points. DTI results revealed altered diffusion in the SRC group along a segment of the corticospinal tract and the superior longitudinal fasciculus in the acute phase of SRC. No differences between the SRC group and control group were seen at follow-up imaging. Conclusions: Acute effects of SRC are associated with both hyperconnectivity and hypoconnectivity, with disruption of white matter integrity. In addition, acute memory performance was most sensitive to these changes. After 21 days, adolescents with SRC returned to baseline performance, although chronic hyperconnectivity of these regions could place these adolescents at greater risk for secondary neuropathological changes, necessitating future follow-up. (JINS, 2018, 24, 781–792)

Keywords

Sports-related concussionAmerican footballAdolescentsResting state fMRIDiffusion imagingLongitudinalMemory
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 24 , Issue 8 , September 2018 , pp. 781 - 792
Copyright
Copyright © The International Neuropsychological Society 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Abbas, K., Shenk, T.E., Poole, V.N., Breedlove, E.L., Leverenz, L.J., Nauman, E.A., & Robinson, M.E. (2015). Alteration of default mode network in high school football athletes due to repetitive subconcussive mild traumatic brain injury: A resting-state functional magnetic resonance imaging study. Brain Connectivity, 5(2), 91–101.Google Scholar
Broyd, S.J., Demanuele, C., Debener, S., Helps, S.K., James, C.J., & Sonuga-Barke, E.J. (2009). Default-mode brain dysfunction in mental disorders: A systematic review. Neuroscience & Biobehavioral Reviews, 33(3), 279–296.Google Scholar
Bryan, M.A., Rowhani-Rahbar, A., Comstock, R.D., & Rivara, F. (2016). Sports-and recreation-related concussions in US youth. Pediatrics, 138(1), e20154635.Google Scholar
Buckner, R.L., & Carroll, D.C. (2007). Self-projection and the brain. Trends in Cognitive Sciences, 11(2), 49–57.Google Scholar
Calhoun, V.D., Adali, T., Pearlson, G.D., & Pekar, J.J. (2001). Spatial and temporal independent component analysis of functional MRI data containing a pair of task‐related waveforms. Human Brain Mapping, 13(1), 43–53.Google Scholar
Calhoun, V.D., Kiehl, K.A., & Pearlson, G.D. (2008). Modulation of temporally coherent brain networks estimated using ICA at rest and during cognitive tasks. Human Brain Mapping, 29(7), 828–838.Google Scholar
Centers for Disease Control and Prevention. (2011). Nonfatal traumatic brain injuries related to sports and recreation activities among persons aged≤19 years---United States, 2001--2009. MMWR: Morbidity and Mortality Weekly Report, 60(39), 1337–1342.Google Scholar
Churchill, N.W., Caverzasi, E., Graham, S.J., Hutchison, M.G., & Schweizer, T.A. (2017). White matter microstructure in athletes with a history of concussion: Comparing diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). Human Brain Mapping, 38, 4201–4211.Google Scholar
Churchill, N., Hutchison, M.G., Leung, G., Graham, S., & Schweizer, T.A. (2017). Changes in functional connectivity of the brain associated with a history of sport concussion: A preliminary investigation. Brain Injury, 31(1), 39–48.Google Scholar
Cubon, V.A., Putukian, M., Boyer, C., & Dettwiler, A. (2011). A diffusion tensor imaging study on the white matter skeleton in individuals with sports-related concussion. Journal of Neurotrauma, 28(2), 189–201.Google Scholar
Czerniak, S.M., Sikoglu, E.M., Navarro, A.A.L., McCafferty, J., Eisenstock, J., Stevenson, J.H., & Moore, C.M. (2015). A resting state functional magnetic resonance imaging study of concussion in collegiate athletes. Brain Imaging and Behavior, 9(2), 323–332.Google Scholar
Dettwiler, A., Murugavel, M., Putukian, M., Cubon, V., Furtado, J., & Osherson, D. (2014). Persistent differences in patterns of brain activation after sports-related concussion: A longitudinal functional magnetic resonance imaging study. Journal of Neurotrauma, 31(2), 180–188.Google Scholar
Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., & Raichle, M.E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America, 102(27), 9673–9678.Google Scholar
Fransson, P., & Marrelec, G. (2008). The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis. NeuroImage, 42(3), 1178–1184.Google Scholar
Gardner, A., Kay-Lambkin, F., Stanwell, P., Donnelly, J., Williams, W.H., Hiles, A., & Jones, D.K. (2012). A systematic review of diffusion tensor imaging findings in sports-related concussion. Journal of Neurotrauma, 29(16), 2521–2538.Google Scholar
Gessel, L.M., Fields, S.K., Collins, C.L., Dick, R.W., & Comstock, R.D. (2007). Concussions among United States high school and collegiate athletes. Journal of Athletic Training, 42(4), 495.Google Scholar
Greicius, M.D., Krasnow, B., Reiss, A.L., & Menon, V. (2003). Functional connectivity in the resting brain: A network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences of the United States of America, 100(1), 253–258.Google Scholar
Griffanti, L., Douaud, G., Bijsterbosch, J., Evangelisti, S., Alfaro-Almagro, F., Glasser, M.F., & Beckmann, C.F. (2017). Hand classification of fMRI ICA noise components. NeuroImage, 154, 188–205.Google Scholar
Guskiewicz, K.M., Weaver, N.L., Padua, D.A., & Garrett, W.E. (2000). Epidemiology of concussion in collegiate and high school football players. The American Journal of Sports Medicine, 28(5), 643–650.Google Scholar
Guskiewicz, K.M., Ross, S.E., & Marshall, S.W. (2001). Postural stability and neuropsychological deficits after concussion in collegiate athletes. Journal of Athletic Training, 36(3), 263.Google Scholar
Guskiewicz, K.M., McCrea, M., Marshall, S.W., Cantu, R.C., Randolph, C., Barr, W., & Kelly, J.P. (2003). Cumulative effects associated with recurrent concussion in collegiate football players: The NCAA Concussion Study. JAMA, 290(19), 2549–2555.Google Scholar
Guskiewicz, K.M., Marshall, S.W., Bailes, J., McCrea, M., Cantu, R.C., Randolph, C., &Jordan, B.D. (2005). Association between recurrent concussion and late-life cognitive impairment in retired professional football players. Neurosurgery, 57(4), 719–726.Google Scholar
Henry, L.C., Tremblay, J., Tremblay, S., Lee, A., Brun, C., Lepore, N., & Lassonde, M. (2011). Acute and chronic changes in diffusivity measures after sports concussion. Journal of Neurotrauma, 28(10), 2049–2059.Google Scholar
Hillary, F.G., & Grafman, J.H. (2017). Injured brains and adaptive networks: The benefits and costs of hyperconnectivity. Trends in Cognitive Sciences, 21(5), 385–401.Google Scholar
Iraji, A., Benson, R.R., Welch, R.D., O’Neil, B.J., Woodard, J.L., Ayaz, S.I., & Liu, T. (2015). Resting state functional connectivity in mild traumatic brain injury at the acute stage: Independent component and seed-based analyses. Journal of Neurotrauma, 32(14), 1031–1045.Google Scholar
Jantzen, K.J., Anderson, B., Steinberg, F.L., & Kelso, J.S. (2004). A prospective functional MR imaging study of mild traumatic brain injury in college football players. AJNR American Journal of Neuroradiology, 25(5), 738–745.Google Scholar
Johnson, B., Zhang, K., Gay, M., Horovitz, S., Hallett, M., Sebastianelli, W., &Slobounov, S. (2012). Alteration of brain default network in subacute phase of injury in concussed individuals: Resting-state fMRI study. NeuroImage, 59(1), 511–518.Google Scholar
Kamins, J., Bigler, E., Covassin, T., Henry, L., Kemp, S., Leddy, J.J., & McLeod, T.C.V. (2017). What is the physiological time to recovery after concussion? A systematic review. British Journal of Sports Medicine, 51(12), 935–940.Google Scholar
Keightley, M.L., Singh Saluja, R., Chen, J.K., Gagnon, I., Leonard, G., Petrides, M., &Ptito, A. (2014). A functional magnetic resonance imaging study of working memory in youth after sports-related concussion: Is it still working? Journal of Neurotrauma, 31(5), 437–451.Google Scholar
Koziol, L.F., Budding, D.E., & Chidekel, D. (2012). From movement to thought: Executive function, embodied cognition, and the cerebellum. The Cerebellum, 11(2), 505–525.Google Scholar
Lancaster, M.A., Olson, D.V., McCrea, M.A., Nelson, L.D., LaRoche, A.A., & Muftuler, L.T. (2016). Acute white matter changes following sport‐related concussion: A serial diffusion tensor and diffusion kurtosis tensor imaging study. Human brain mapping, 37(11), 3821–3834. Google Scholar
Lau, B.C., Collins, M.W., & Lovell, M.R. (2011). Cutoff scores in neurocognitive testing and symptom clusters that predict protracted recovery from concussions in high school athletes. Neurosurgery, 70(2), 371–379.Google Scholar
Li, Y.O., Adalı, T., & Calhoun, V.D. (2007). Estimating the number of independent components for functional magnetic resonance imaging data. Human Brain Mapping, 28(11), 1251–1266.Google Scholar
Lovell, M. (2015). ImPACT: An evidence-based and comprehensive concussion management program. ImPACT Research Report, 3, 1–2.Google Scholar
Manto, M., Bower, J.M., Conforto, A.B., Delgado-García, J.M., da Guarda, S.N.F., Gerwig, M., & Molinari, M. (2012). Consensus paper: Roles of the cerebellum in motor control—the diversity of ideas on cerebellar involvement in movement. The Cerebellum, 11(2), 457–487.Google Scholar
Maugans, T.A., Farley, C., Altaye, M., Leach, J., & Cecil, K.M. (2012). Pediatric sports-related concussion produces cerebral blood flow alterations. Pediatrics, 129(1), 28–37.Google Scholar
Mayer, A.R., Mannell, M.V., Ling, J., Gasparovic, C., & Yeo, R.A. (2011). Functional connectivity in mild traumatic brain injury. Human Brain Mapping, 32(11), 1825–1835.Google Scholar
McCrea, M., Guskiewicz, K.M., Marshall, S.W., Barr, W., Randolph, C., Cantu, R.C., & Kelly, J.P. (2003). Acute effects and recovery time following concussion in collegiate football players: The NCAA Concussion Study. JAMA, 290(19), 2556–2563.Google Scholar
McCrory, P., Meeuwisse, W., Aubry, M., Cantu, B., Dvorak, J., Echemendia, R., & Sills, A. (2013). Consensus statement on concussion in sport—the 4th International Conference on Concussion in Sport held in Zurich, November 2012. Journal of Science and Medicine in Sport, 16(3), 178–189.Google Scholar
Meier, T.B., Bellgowan, P.S., & Mayer, A.R. (2017). Longitudinal assessment of local and global functional connectivity following sports-related concussion. Brain Imaging and Behavior, 11(1), 129–140.Google Scholar
Murugavel, M., Cubon, V., Putukian, M., Echemendia, R., Cabrera, J., Osherson, D., &Dettwiler, A. (2014). A longitudinal diffusion tensor imaging study assessing white matter fiber tracts after sports-related concussion. Journal of Neurotrauma, 31(22), 1860–1871.Google Scholar
Oouchi, H., Yamada, K., Sakai, K., Kizu, O., Kubota, T., Ito, H., &Nishimura, T. (2007). Diffusion anisotropy measurement of brain white matter is affected by voxel size: Underestimation occurs in areas with crossing fibers. AJNR American Journal of Neuroradiology, 28(6), 1102–1106.Google Scholar
Orr, C.A., Albaugh, M.D., Watts, R., Garavan, H., Andrews, T., Nickerson, J.P., & Hudziak, J.J. (2016). Neuroimaging biomarkers of a history of concussion observed in asymptomatic young athletes. Journal of Neurotrauma, 33(9), 803–810.Google Scholar
Pruim, R.H., Mennes, M., Buitelaar, J.K., & Beckmann, C.F. (2015). Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI. NeuroImage, 112, 278–287.Google Scholar
Raichle, M.E., & Snyder, A.Z. (2007). A default mode of brain function: A brief history of an evolving idea. NeuroImage, 37(4), 1083–1090.Google Scholar
Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., & Shulman, G.L. (2001). A default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America, 98(2), 676–682.Google Scholar
Smith, E.E., & Jonides, J. (1998). Neuroimaging analyses of human working memory. Proceedings of the National Academy of Sciences of the United States of America, 95(20), 12061–12068.Google Scholar
Stevens, M.C., Lovejoy, D., Kim, J., Oakes, H., Kureshi, I., & Witt, S.T. (2012). Multiple resting state network functional connectivity abnormalities in mild traumatic brain injury. Brain Imaging and Behavior, 6, 293–318.Google Scholar
Toledo, E., Lebel, A., Becerra, L., Minster, A., Linnman, C., Maleki, N., & Borsook, D. (2012). The young brain and concussion: Imaging as a biomarker for diagnosis and prognosis. Neuroscience & Biobehavioral Reviews, 36(6), 1510–1531.Google Scholar
Virji-Babul, N., Borich, M.R., Makan, N., Moore, T., Frew, K., Emery, C.A., &Boyd, L.A. (2013). Diffusion tensor imaging of sports-related concussion in adolescents. Pediatric Neurology, 48(1), 24–29.Google Scholar
Virji-Babul, N., Hilderman, C. G., Makan, N., Liu, A., Smith-Forrester, J., Franks, C., & Wang, Z. J. (2014). Changes in functional brain networks following sports-related concussion in adolescents. Journal of neurotrauma, 31(23), 1914–1919.Google Scholar
Yeh, F.C., Wedeen, V.J., & Tseng, W.Y.I. (2010). Generalized q-sampling imaging. IEEE Transactions on Medical Imaging, 29(9), 1626–1635.Google Scholar
Yeh, F.C., Tang, P.F., & Tseng, W.Y.I. (2013). Diffusion MRI connectometry automatically reveals affected fiber pathways in individuals with chronic stroke. Neuroimage: Clinical, 2, 912–921.Google Scholar
Yeh, F.C., Verstynen, T.D., Wang, Y., Fernández-Miranda, J.C., & Tseng, W.Y.I. (2013). Deterministic diffusion fiber tracking improved by quantitative anisotropy. PLoS One, 8(11), e80713.Google Scholar
Yeh, F.C., Badre, D., & Verstynen, T. (2016). Connectometry: A statistical approach harnessing the analytical potential of the local connectome. NeuroImage, 125, 162–171.Google Scholar
Yuh, E.L., Hawryluk, G.W., & Manley, G.T. (2014). Imaging concussion: A review. Neurosurgery, 75(Suppl 4), S50–S63.Google Scholar
Zhang, K., Johnson, B., Pennell, D., Ray, W., Sebastianelli, W., & Slobounov, S. (2010). Are functional deficits in concussed individuals consistent with white matter structural alterations: Combined FMRI & DTI study. Experimental Brain Research, 204(1), 57–70.Google Scholar
Supplementary material: File

Murdaugh et. al. supplementary material

Figures S1-S3 and Table S1

Download Murdaugh et. al. supplementary material(File)
File 1.9 MB