Increased sensitivity to traumatic axonal injury on postconcussion diffusion tensor imaging scans in National Football League players by using premorbid baseline scans

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  • 1 Departments of Radiology and
  • 3 Neurological Surgery, Weill Cornell Medicine, New York, New York;
  • 2 Department of Neurological Surgery, New Hampshire NeuroSpine Institute, Bedford, New Hampshire;
  • 4 Departments of Neurology and
  • 7 Orthopedic Surgery, Sports Medicine Hospital for Special Surgery, New York, New York;
  • 5 Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, Florida; and
  • 6 New York Football Giants, East Rutherford, New Jersey
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OBJECTIVE

Statistical challenges exist when using diffusion tensor imaging (DTI) to assess traumatic axonal injury (TAI) in individual concussed athletes. The authors examined active professional American football players over a 6-year time period to study potential TAI after concussion and assess optimal methods to analyze DTI at the individual level.

METHODS

Active American professional football players recruited prospectively were assessed with DTI, conventional MRI, and standard clinical workup. Subjects underwent an optional preseason baseline scan and were asked to undergo a scan within 5 days of concussion during gameplay. DTI from 25 age- and sex-matched controls were obtained. Both semiautomated region-of-interest analysis and fully automated tract-based spatial statistics (TBSS) were used to examine DTI at individual and group levels. Statistical differences were assessed comparing individual DTI data to baseline imaging versus a normative database. Group-level comparisons were also performed to determine if longer exposure to professional-level play or prior concussion cause white matter microstructural integrity changes.

RESULTS

Forty-nine active professional football players were recruited into the study. Of the 49 players, 7 were assessed at baseline during the preseason and after acute concussion. An additional 18 players were assessed after acute concussion only. An additional 24 players had only preseason baseline assessments. The results suggest DTI is more sensitive to suspected TAI than conventional MRI, given that 4 players demonstrated decreased fractional anisotropy (FA) in multiple tracts despite normal conventional MRI. Furthermore, the data suggest individual assessment of DTI data using baseline premorbid imaging is more sensitive than typical methods of comparing data to a normative control group. Among all subjects with baseline data, 1 reduced FA tract (± 2.5 standard deviations) was found using the typical normative database reference versus 10 statistically significant (p < 0.05) reduced FA tracts when referencing internal control baseline data. All group-level comparisons were statistically insignificant (p > 0.05).

CONCLUSIONS

Baseline premorbid DTI data for individual DTI analysis provides increased statistical sensitivity. Specificity using baseline imaging also increases because numerous potential etiologies for reduced FA may exist prior to a concussion. These data suggest that there is a high potential for false-positive and false-negative assessment of DTI data using typical methods of comparing an individual to normative groups given the variability of FA values in the normal population.

ABBREVIATIONS AAN = American Academy of Neurology; ACR = anterior corona radiata; DTI = diffusion tensor imaging; DVA = developmental venous anomaly; FA = fractional anisotropy; FOV = field of view; ImPACT = Immediate Post-Concussion Assessment and Cognitive Test; mTBI = mild TBI; NFL = National Football League; NFLPA = NFL Players Association; ROI = region of interest; ROQS = Reproducible Objective Quantification Scheme; SCR = superior corona radiata; SRC = sports-related concussion; TAI = traumatic axonal injury; TBI = traumatic brain injury; TBSS = tract-based spatial statistics; UF = uncinate fasciculus.

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Contributor Notes

Correspondence Sumit N. Niogi: Weill Cornell Medicine, New York, NY. sun2003@med.cornell.edu.

ACCOMPANYING EDITORIAL DOI: 10.3171/2019.5.JNS19892.

INCLUDE WHEN CITING Published online September 6, 2019; DOI: 10.3171/2019.3.JNS181864.

Disclosures Dr. Niogi is the inventor of the Reproducible Objective Quantification Scheme (ROQS); Cornell licensed ROQS to MRIBank, LLC. Dr. Shetty serves on the GE-NFL Medical Advisory Board and has research grants from the GE-NFL fund, ElMindA Ltd., Chembio/Perseus, and Teva Pharmaceuticals. Dr. Hartl reports being a consultant to DePuy-Synthes, Ulrich, and BrainLAB, and receiving royalties from Zimmer Biomet. Dr. Warren serves on the Board of Orthonet.

  • 1

    Azouvi P, Arnould A, Dromer E, Vallat-Azouvi C: Neuropsychology of traumatic brain injury: an expert overview. Rev Neurol (Paris) 173:461472, 2017

    • Search Google Scholar
    • Export Citation
  • 2

    Bahrami N, Sharma D, Rosenthal S, Davenport EM, Urban JE, Wagner B, : Subconcussive head impact exposure and white matter tract changes over a single season of youth football. Radiology 281:919926, 2016

    • Search Google Scholar
    • Export Citation
  • 3

    Baliyan V, Das CJ, Sharma R, Gupta AK: Diffusion weighted imaging: technique and applications. World J Radiol 8:785798, 2016

  • 4

    Daneshvar DH, Nowinski CJ, McKee AC, Cantu RC: The epidemiology of sport-related concussion. Clin Sports Med 30:117, vii, 2011

  • 5

    Davenport EM, Whitlow CT, Urban JE, Espeland MA, Jung Y, Rosenbaum DA, : Abnormal white matter integrity related to head impact exposure in a season of high school varsity football. J Neurotrauma 31:16171624, 2014

    • Search Google Scholar
    • Export Citation
  • 6

    Davies CR, Harrington JJ: Impact of obstructive sleep apnea on neurocognitive function and impact of continuous positive air pressure. Sleep Med Clin 11:287298, 2016

    • Search Google Scholar
    • Export Citation
  • 7

    Delouche A, Attyé A, Heck O, Grand S, Kastler A, Lamalle L, : Diffusion MRI: pitfalls, literature review and future directions of research in mild traumatic brain injury. Eur J Radiol 85:2530, 2016

    • Search Google Scholar
    • Export Citation
  • 8

    Gardner A, Kay-Lambkin F, Stanwell P, Donnelly J, Williams WH, Hiles A, : A systematic review of diffusion tensor imaging findings in sports-related concussion. J Neurotrauma 29:25212538, 2012

    • Search Google Scholar
    • Export Citation
  • 9

    Hutchinson EB, Schwerin SC, Avram AV, Juliano SL, Pierpaoli C: Diffusion MRI and the detection of alterations following traumatic brain injury. J Neurosci Res 96:612625, 2018

    • Search Google Scholar
    • Export Citation
  • 10

    Iverson GL, Gardner AJ, Terry DP, Ponsford JL, Sills AK, Broshek DK, : Predictors of clinical recovery from concussion: a systematic review. Br J Sports Med 51:941948, 2017

    • Search Google Scholar
    • Export Citation
  • 11

    Koerte IK, Ertl-Wagner B, Reiser M, Zafonte R, Shenton ME: White matter integrity in the brains of professional soccer players without a symptomatic concussion. JAMA 308:18591861, 2012

    • Search Google Scholar
    • Export Citation
  • 12

    Lerner A, Mogensen MA, Kim PE, Shiroishi MS, Hwang DH, Law M: Clinical applications of diffusion tensor imaging. World Neurosurg 82:96109, 2014

    • Search Google Scholar
    • Export Citation
  • 13

    Makdissi M: Is the simple versus complex classification of concussion a valid and useful differentiation? Br J Sports Med 43 (Suppl 1):i23i27, 2009

    • Search Google Scholar
    • Export Citation
  • 14

    Mustafi SM, Harezlak J, Koch KM, Nencka AS, Meier TB, West JD, : Acute white-matter abnormalities in sports-related concussion: a diffusion tensor imaging study from the NCAA-DoD CARE Consortium. J Neurotrauma 35:26532664, 2018

    • Search Google Scholar
    • Export Citation
  • 15

    Niogi SN, Mukherjee P: Diffusion tensor imaging of mild traumatic brain injury. J Head Trauma Rehabil 25:241255, 2010

  • 16

    Niogi SN, Mukherjee P, Ghajar J, Johnson C, Kolster RA, Sarkar R, : Extent of microstructural white matter injury in postconcussive syndrome correlates with impaired cognitive reaction time: a 3T diffusion tensor imaging study of mild traumatic brain injury. AJNR Am J Neuroradiol 29:967973, 2008

    • Search Google Scholar
    • Export Citation
  • 17

    Niogi SN, Mukherjee P, Ghajar J, Johnson CE, Kolster R, Lee H, : Structural dissociation of attentional control and memory in adults with and without mild traumatic brain injury. Brain 131:32093221, 2008

    • Search Google Scholar
    • Export Citation
  • 18

    Niogi SN, Mukherjee P, McCandliss BD: Diffusion tensor imaging segmentation of white matter structures using a Reproducible Objective Quantification Scheme (ROQS). Neuroimage 35:166174, 2007

    • Search Google Scholar
    • Export Citation
  • 19

    Reddy CC, Collins MW: Sports concussion: management and predictors of outcome. Curr Sports Med Rep 8:1015, 2009

  • 20

    Sasaki T, Pasternak O, Mayinger M, Muehlmann M, Savadjiev P, Bouix S, : Hockey Concussion Education Project, Part 3. White matter microstructure in ice hockey players with a history of concussion: a diffusion tensor imaging study. J Neurosurg 120:882890, 2014

    • Search Google Scholar
    • Export Citation
  • 21

    Scheid R, Preul C, Gruber O, Wiggins C, von Cramon DY: Diffuse axonal injury associated with chronic traumatic brain injury: evidence from T2*-weighted gradient-echo imaging at 3 T. AJNR Am J Neuroradiol 24:10491056, 2003

    • Search Google Scholar
    • Export Citation
  • 22

    Shenton ME, Hamoda HM, Schneiderman JS, Bouix S, Pasternak O, Rathi Y, : A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury. Brain Imaging Behav 6:137192, 2012

    • Search Google Scholar
    • Export Citation
  • 23

    Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, : Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31:14871505, 2006

    • Search Google Scholar
    • Export Citation
  • 24

    Steenerson K, Starling AJ: Pathophysiology of sports-related concussion. Neurol Clin 35:403408, 2017

  • 25

    Sundgren PC, Dong Q, Gómez-Hassan D, Mukherji SK, Maly P, Welsh R: Diffusion tensor imaging of the brain: review of clinical applications. Neuroradiology 46:339350, 2004

    • Search Google Scholar
    • Export Citation
  • 26

    Watts R, Thomas A, Filippi CG, Nickerson JP, Freeman K: Potholes and molehills: bias in the diagnostic performance of diffusion-tensor imaging in concussion. Radiology 272:217223, 2014

    • Search Google Scholar
    • Export Citation
  • 27

    Zhang L, Heier LA, Zimmerman RD, Jordan B, Uluǧ AM: Diffusion anisotropy changes in the brains of professional boxers. AJNR Am J Neuroradiol 27:20002004, 2006

    • Search Google Scholar
    • Export Citation
  • 28

    Zhang L, Ravdin LD, Relkin N, Zimmerman RD, Jordan B, Lathan WE, : Increased diffusion in the brain of professional boxers: a preclinical sign of traumatic brain injury? AJNR Am J Neuroradiol 24:5257, 2003

    • Search Google Scholar
    • Export Citation

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