Stability of MRI metrics in the advanced research core of the NCAA-DoD concussion assessment, research and education (CARE) consortium

  • Andrew S. Nencka
  • Timothy B. Meier
  • Yang Wang
  • L. Tugan Muftuler
  • Yu-Chien Wu
  • Andrew J. Saykin
  • Jaroslaw Harezlak
  • M. Alison Brooks
  • Christopher C. Giza
  • John Difiori
  • Kevin M. Guskiewicz
  • Jason P. Mihalik
  • Stephen M. LaConte
  • Stefan M. Duma
  • Steven Broglio
  • Thomas McAllister
  • Michael A. McCrea
  • Kevin M. Koch
Original Research

Abstract

The NCAA-DoD Concussion Assessment, Research, and Education (CARE) consortium is performing a large-scale, comprehensive study of sport related concussions in college student-athletes and military service academy cadets. The CARE “Advanced Research Core” (ARC), is focused on executing a cutting-edge investigative protocol on a subset of the overall CARE athlete population. Here, we present the details of the CARE ARC MRI acquisition and processing protocol along with preliminary analyzes of within-subject, between-site, and between-subject stability across a variety of MRI biomarkers. Two experimental datasets were utilized for this analysis. First, two “human phantom” subjects were imaged multiple times at each of the four CARE ARC imaging sites, which utilize equipment from two imaging vendors. Additionally, a control cohort of healthy athletes participating in non-contact sports were enrolled in the study at each CARE ARC site and imaged at four time points. Multiple morphological image contrasts were acquired in each MRI exam; along with quantitative diffusion, functional, perfusion, and relaxometry imaging metrics. As expected, the imaging markers were found to have varying levels of stability throughout the brain. Importantly, between-subject variance was generally found to be greater than within-subject and between-site variance. These results lend support to the expectation that cross-site and cross-vendor advanced quantitative MRI metrics can be utilized to improve analytic power in assessing sensitive neurological variations; such as those effects hypothesized to occur in sports-related-concussion. This stability analysis provides a crucial foundation for further work utilizing this expansive dataset, which will ultimately be freely available through the Federal Interagency Traumatic Brain Injury Research Informatics System.

Keywords

MRI Stability Reproducibility Quantitative imaging Concussion mTBI 

Notes

Acknowledgments

This project was funded with support from the Grand Alliance Concussion Assessment, Research, and Education (CARE) Consortium, funded, in part by the National Collegiate Athletic Association (NCAA) and the Department of Defense (DOD). The U.S. Army Medical Research Acquisition Activity, 820 Chandler Street, Fort Detrick MD 21702-5014 is the awarding and administering acquisition office. This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Psychological Health and Traumatic Brain Injury Program under Award NO W81XWH-14-2-0151. Opinions, interpretations, conclusions and recommendations are those of the author and are not necessarily endorsed by the Department of Defense (DHP funds). The authors would like to thank Jenelle E. Fuller, Haley M. Cilliers, Martha Garcia, Sara John, Nana Asiedu, Liga Blyholder, Mike Powers, Morgan Shields, Briana Meyer, Sonal Singh, Zoey Wang, Mania Alexandria, Max Zeiger, Alma Martinez, Douglas Chan, Brennan Delattre, Jonathan Lisinski, Christopher Anzalone, Amber Leinwand, April ‘Nikki’ Jennings, Sharon Bryan, Victor Wright, Jennifer Franco, Issack Boru, Corey Rodrigo, Parker Traugot, Grant Cabell, Erin Grand, Aliza Nedimyer, and Tricia Combs for data acquisition and Brad Swearingen, Lezlie Espana, and Robin Karr for algorithm support.

Supplementary material

11682_2017_9775_MOESM1_ESM.pdf (118 kb)
Supplementary material 1 (PDF 118 KB)

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Andrew S. Nencka
    • 1
  • Timothy B. Meier
    • 2
  • Yang Wang
    • 1
  • L. Tugan Muftuler
    • 2
  • Yu-Chien Wu
    • 3
  • Andrew J. Saykin
    • 3
  • Jaroslaw Harezlak
    • 4
  • M. Alison Brooks
    • 5
  • Christopher C. Giza
    • 6
  • John Difiori
    • 7
  • Kevin M. Guskiewicz
    • 8
  • Jason P. Mihalik
    • 8
  • Stephen M. LaConte
    • 9
  • Stefan M. Duma
    • 10
  • Steven Broglio
    • 11
  • Thomas McAllister
    • 12
  • Michael A. McCrea
    • 2
  • Kevin M. Koch
    • 1
  1. 1.Department of RadiologyMedical College of WisconsinMilwaukeeUSA
  2. 2.Department of NeurosurgeryMedical College of WisconsinMilwaukeeUSA
  3. 3.Department of Radiology and Imaging ScienceIndiana University School of MedicineIndianapolisUSA
  4. 4.Department of Epidemiology and BiostatisticsIndiana UniversityBloomingtonUSA
  5. 5.Department of Orthopedics and RehabilitationUniversity of Wisconsin School of Medicine and Public HealthMadisonUSA
  6. 6.Department of Pediatrics and Neurosurgery, UCLA Steve Tisch BrainSPORT ProgramUniversity of California Los AngelesLos AngelesUSA
  7. 7.Department of OrthopedicsUniversity of California Los AngelesLos AngelesUSA
  8. 8.Department of Exercise and Sport ScienceUniversity of North CarolinaChapel HillUSA
  9. 9.Virginia Tech Carilon Research InstituteVirginia TechBlacksburgUSA
  10. 10.Institute for Critical Technology and Applied ScienceVirginia TechBlacksburgUSA
  11. 11.Department of KinesiologyUniversity of MichiganAnn ArborUSA
  12. 12.Department of PsychiatryIndiana University School of MedicineBloomingtonUSA

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